Fibroblast Insights into the Pathogenesis of Ankylosing Spondylitis

Ankylosing spondylitis: From pathogenesis to therapy

Ankylosing spondylitis (AS) is an autoimmune rheumatic disease that primarily affects the axial joints, with its etiology complex and still not fully understood. The unknown pathogenesis of AS limits the development of treatment strategies, so keeping up-to-date with the current research on AS can help in searching for potential therapeutic targets. In addition to the classic HLA-B27 genetic susceptibility and Th17-related inflammatory signals, increasing research is focusing on the influence of autoantigen-centered autoimmune responses and bone stromal cells on the onset of AS. Autoantigens derived from gut microbiota and preferential TCR both exacerbate the autoimmune response in patients with AS. Furthermore, dysregulated bone metabolism also promotes pathological new bone formation in AS. Current treatments approved for AS almost focus on the management of inflammation with inconsistent treatment results due to the heterogeneity of patients. In this review, we systematically summarized various pathogenesis and management of AS, meanwhile discussed the underlying risk factors and potential therapeutic targets.

Research Progress of Fibroblasts in Human Diseases

Fibroblasts, which originate from embryonic mesenchymal cells, are the predominant cell type seen in loose connective tissue. As the main components of the internal environment that cells depend on for survival, fibroblasts play an essential role in tissue development, wound healing, and the maintenance of tissue homeostasis. Furthermore, fibroblasts are also involved in several pathological processes, such as fibrosis, cancers, and some inflammatory diseases. In this review, we analyze the latest research progress on fibroblasts, summarize the biological characteristics and physiological functions of fibroblasts, and delve into the role of fibroblasts in disease pathogenesis and explore treatment approaches for fibroblast-related diseases.

A systematic review and meta-analysis of the efficacy and safety of iguratimod in the treatment of inflammatory arthritis and degenerative arthritis

Objective

To assess the efficacy and safety of iguratimod (IGU) in the treatment of inflammatory arthritis and degenerative arthritis.

Methods

Initially, randomized controlled trials (RCTs) on using IGU in treating inflammatory arthritis and degenerative arthritis were systematically gathered from various databases up to February 2024. Subsequently, two researchers independently screened the literature, extracted data, assessed the risk of bias in included studies, and conducted a meta-analysis using RevMan 5.4 software.

Results

Fifty-four RCTs involving three inflammatory arthritis were included, including ankylosing spondylitis (AS), osteoarthritis (OA), and rheumatoid arthritis (RA). For AS, the meta-analysis results showed that IGU may decrease BASDAI (SMD -1.68 [-2.32, -1.03], P < 0.00001) and BASFI (WMD -1.29 [-1.47, -1.11], P < 0.00001); IGU may also decrease inflammatory factor [ESR: (WMD -10.33 [-14.96, -5.70], P < 0.0001); CRP: (WMD -10.11 [-14.55, -5.66], P < 0.00001); TNF-α: (WMD -6.22 [-7.97, -4.47], P < 0.00001)]. For OA, the meta-analysis results showed that IGU may decrease VAS (WMD -2.20 [-2.38, -2.01], P < 0.00001) and WOMAC (WMD -7.27 [-12.31, -2.24], P = 0.005); IGU may also decrease IL-6 (WMD -8.72 [-10.00, -7.45], P < 0.00001). For RA, the meta-analysis results showed that IGU may improve RA remission rate [ACR20: (RR 1.18 [1.02, 1.35], P = 0.02); ACR50: (RR 1.32 [1.05, 1.64], P = 0.02); ACR70: (RR 1.44 [1.02, 2.04], P = 0.04)] and decrease DAS28 (WMD -0.92 [-1.20, -0.63], P < 0.00001); IGU may also decrease inflammatory factors [CRP: (SMD -1.36 [-1.75, -0.96], P < 0.00001); ESR: (WMD -9.09 [-11.80, -6.38], P < 0.00001); RF: (SMD -1.21 [-1.69, -0.73], P < 0.00001)]. Regarding safety, adding IGU will not increase the incidence of adverse events.

Conclusion

IGU might emerge as a promising and secure therapeutic modality for addressing AS, OA, and RA.

Systematic Review Registration

Identifier PROSPERO: CRD42021289249.

Environmental and Genetic Determinants of Ankylosing Spondylitis

Exposure to heavy metals and lifestyle factors like smoking contribute to the production of free oxygen radicals. This fact, combined with a lowered total antioxidant status, can induce even more damage in the development of ankylosing spondylitis (AS). Despite the fact that some researchers are looking for more genetic factors underlying AS, most studies focus on polymorphisms within the genes encoding the human leukocyte antigen (HLA) system. The biggest challenge is finding the effective treatment of the disease. Genetic factors and the influence of oxidative stress, mineral metabolism disorders, microbiota, and tobacco smoking seem to be of great importance for the development of AS. The data contained in this review constitute valuable information and encourage the initiation and development of research in this area, showing connections between inflammatory disorders leading to the pathogenesis of AS and selected environmental and genetic factors.

Genetic associations in ankylosing spondylitis: circulating proteins as drug targets and biomarkers

Background

Ankylosing spondylitis (AS) is a complex condition with a significant genetic component. This study explored circulating proteins as potential genetic drug targets or biomarkers to prevent AS, addressing the need for innovative and safe treatments.

Methods

We analyzed extensive data from protein quantitative trait loci (pQTLs) with up to 1,949 instrumental variables (IVs) and selected the top single-nucleotide polymorphism (SNP) associated with AS risk. Utilizing a two-sample Mendelian randomization (MR) approach, we assessed the causal relationships between identified proteins and AS risk. Colocalization analysis, functional enrichment, and construction of protein-protein interaction networks further supported these findings. We utilized phenome-wide MR (phenMR) analysis for broader validation and repurposing of drugs targeting these proteins. The Drug-Gene Interaction database (DGIdb) was employed to corroborate drug associations with potential therapeutic targets. Additionally, molecular docking (MD) techniques were applied to evaluate the interaction between target protein and four potential AS drugs identified from the DGIdb.

Results

Our analysis identified 1,654 plasma proteins linked to AS, with 868 up-regulated and 786 down-regulated. 18 proteins (AGER, AIF1, ATF6B, C4A, CFB, CLIC1, COL11A2, ERAP1, HLA-DQA2, HSPA1L, IL23R, LILRB3, MAPK14, MICA, MICB, MPIG6B, TNXB, and VARS1) that show promise as therapeutic targets for AS or biomarkers, especially MAPK14, supported by evidence of colocalization. PhenMR analysis linked these proteins to AS and other diseases, while DGIdb analysis identified potential drugs related to MAPK14. MD analysis indicated strong binding affinities between MAPK14 and four potential AS drugs, suggesting effective target-drug interactions.

Conclusion

This study underscores the utility of MR analysis in AS research for identifying biomarkers and therapeutic drug targets. The involvement of Th17 cell differentiation-related proteins in AS pathogenesis is particularly notable. Clinical validation and further investigation are essential for future applications.

A review of long non-coding RNAs in ankylosing spondylitis: pathogenesis, clinical assessment, and therapeutic targets

Ankylosing spondylitis (AS) is a chronic immune-mediated type of inflammatory arthritis characterized by inflammation, bone erosion, and stiffness of the spine and sacroiliac joints. Despite great efforts put into the investigation of the disease, the pathogenesis of AS remains unclear, posing challenges in identifying ideal targets for diagnosis and treatment. To enhance our understanding of AS, an increasing number of studies have been conducted. Some of these studies reveal that long non-coding RNAs (lncRNAs) play crucial roles in the etiology of AS. Some certain lncRNAs influence the development of AS by regulating inflammatory responses, autophagy, apoptosis, and adipogenesis, as well as the proliferation and differentiation of cells. Additionally, some lncRNAs demonstrate potential as biomarkers, aiding in monitoring disease progression and predicting prognosis. In this review, we summarize recent studies concerning lncRNAs in AS to elucidate the underlying mechanisms in which lncRNAs are involved and their potential values as biomarkers for disease assessment and druggable targets for therapy.

Analysis of m6A regulators related immune characteristics in ankylosing spondylitis by integrated bioinformatics and computational strategies

N6-methyladenosine (m6A) modification, as a common epigenetic modification, has been widely studied in autoimmune diseases. However, the role of m6A in the regulation of the immune microenvironment of ankylosing spondylitis (AS) remains unclear. Therefore, we aimed to investigate the effect of m6A modification on the immune microenvironment of AS. We first evaluated RNA modification patterns mediated by 26 m6A regulators in 52 AS samples and 20 healthy samples. Thereafter, an m6A related classifier composed of seven genes was constructed and could effectively distinguish healthy and AS samples. Then, the correlation between m6A regulators and immune characteristics were investigated, including infiltrating immunocytes, immune reactions activity, and human leukocyte antigen (HLA) genes expression. The results indicated that m6A regulators was closely correlated with immune characteristics. For example, EIF3A was significantly related to infiltrating immunocytes; IGF2BP2 and EIF3A were significant regulators in immune reaction of TGF-β family member, and the expression of HLA-DPA1 and HLA-E were affected by EIF3A and ALKBH5. Next, two distinct m6A expression patterns were identified through unsupervised clustering analysis, and diverse immune characteristics were found between them. A total of 5889 m6A phenotype-related genes were obtained between the two expression patterns, and their biological functions were revealed. Finally, we validated the expression status of m6A modification regulators using two additional datasets. Our findings illustrate that m6A modifications play a critical role in the diversity and complexity of the AS immune microenvironment.