Role of the microbiome and its metabolites in ankylosing spondylitis

Integration of Metabolomics and 16S Ribosomal RNA Sequencing to Elucidate the Pathogenesis of Ankylosing Spondylitis

OBJECTIVE

Despite growing interest in the gut microbiota and blood metabolome in patients with ankylosing spondylitis (AS), its role remains poorly understood. Here, we investigate how microbial and metabolic alterations contribute to AS.

METHODS

Fecal microbiome data from 40 AS patients were compared with those from 40 healthy controls (HCs) using 16S ribosomal RNA (rRNA) gene sequencing. The plasma metabolic profiles were analyzed and integrated with the microbiota data to identify biological characteristics specific to AS.

RESULTS

AS patients showed significant enrichment of specific genera, including Megamonas, Elusimicrobium, Dysgonomonas, Ruminococcus_gauvreauii_group, and unclassified_Prevotellaceae. Pathways with the most differentially expressed metabolites included bile secretion; neomycin, kanamycin, and gentamicin biosynthesis; and arachidonic acid metabolism. Positive correlations between Megamonas and Elusimicrobium and metabolites such as piribedil, l-cystathionine, and crocetin dialdehyde suggested microbial enrichment in AS patients.

CONCLUSIONS

A disrupted gut microbiota and altered metabolites are present in AS patients. Integrating microbiome and metabolomic data reveals significant disruptions in AS patients, improving our understanding of its pathogenesis.

The Gut Feeling: The Role of Gut Microbiome in Orthopedics

Introduction: Advancements in microbiome-targeted therapies, including probiotics, prebiotics, and fecal microbial transplantation, offer exciting possibilities for orthopedic care. Probiotics, live beneficial microorganisms found in fermented foods, such as yogurt, kefir, sauerkraut, kimchi, and cheese, help maintain a healthy gut microbiome. Prebiotics and fiber-rich foods such as onions, garlic, and whole grains, nourish these bacteria, supporting their growth and activity. Together, these therapies regulate gut health, promote immune resilience, reduce infection risks, and accelerate healing – key factors in orthopedic outcomes [1, 2]. The gut microbiome, a diverse ecosystem of microorganisms, plays a pivotal role in maintaining overall health [3]. Beyond digestion, it influences immune regulation, inflammation control, and musculoskeletal well-being [4]. Gut health significantly impacts orthopedic outcomes, including infection control, bone healing, and maintaining bone density. An imbalance in this ecosystem, known as dysbiosis, can compromise recovery and increase infection risks [5]. Supporting gut health through dietary modifications, probiotics, or prebiotics holds the potential to enhance patient outcomes [6]. Orthopedic Infections and Gut Health: Periprosthetic joint infections and fracture-related infections remain formidable challenges in orthopedic care. Biofilm formation on implants can protect bacteria from antibiotics and immune responses, complicating treatment [7]. Dysbiosis can further exacerbate these risks by allowing bacteria to enter the bloodstream and colonize surgical sites [8]. Maintaining a balanced gut microbiome can enhance the body’s immune defenses, limit bacterial migration, and promote implant longevity. Fracture Healing and Microbial Influence: Bone repair is a finely regulated process involving inflammation, new bone formation, and remodeling [9]. A healthy gut microbiome plays an essential role in managing this process by moderating inflammation and promoting bone cell activity. Disruptions to the microbial ecosystem can lead to excessive inflammation and hinder the body’s ability to heal effectively [10]. Supporting microbial health may improve healing outcomes for patients prone to delayed recovery or complications. Autoimmune Conditions and Increased Susceptibility to Infection: Autoimmune diseases, such as rheumatoid arthritis, heighten susceptibility to infections due to weakened immune function [11]. Dysbiosis can further worsen immune imbalance, increasing the risk of bacterial migration to surgical sites. Ensuring gut health may help fortify immune resilience and reduce post-surgical complications for patients with these conditions [12]. Pain Management and Microbiome Modulation: The gut microbiome affects pain perception by influencing the production of neurotransmitters that regulate pain pathways. An imbalance in gut bacteria can lead to heightened pain sensitivity, posing challenges for managing chronic conditions such as osteoarthritis [13]. Optimizing gut health may offer an additional approach to complement traditional pain management strategies and reduce dependency on medications. Bone Density and Mineral Absorption The gut microbiome plays a critical role in absorbing minerals vital for maintaining bone strength and density. Disruptions in microbial balance can impair this absorption process, contributing to conditions such as osteoporosis [14]. Emerging research suggests that specific probiotics may help enhance mineral absorption, providing a supportive therapy for improving bone health and reducing fracture risk [15]. Post-Surgical Recovery and Systemic Health: The influence of the gut microbiome extends beyond local sites, playing a key role in systemic recovery following surgery. A balanced microbiome supports faster healing, reduced inflammation, and fewer post-operative complications. Conversely, microbial imbalances can delay recovery and increase the risk of infections [16]. Strategies to maintain microbial health in the perioperative period may improve surgical outcomes and accelerate rehabilitation. Innovative Approaches in Orthopedic Care: Screening for microbial imbalances before surgery could allow for timely interventions, minimizing complications and improving outcomes. While some therapies remain experimental, they represent promising avenues for future developments in personalized orthopedic treatment strategies [17]. Recent research has revealed that gut microbial alterations, particularly those affecting arginine metabolism, play a significant role in influencing bone structural remodeling [18]. Mechanical loading is crucial for maintaining bone health, but its effectiveness is often hampered by high variability in bone mechanoreceptor activity influenced by gut microbes. Studies have shown that microbial depletion can profoundly influence this responsiveness, indicating a possible pathway for future therapeutic strategies. The gut-bone axis, a concept gaining increasing attention, connects the state of the microbiome with bone health [19]. This relationship opens up the potential for microbiome-targeted interventions, such as dietary changes or probiotics, to enhance bone strength and treat conditions such as osteoporosis and inflammatory arthritis. By understanding the microbial factors that influence bone metabolism, researchers are uncovering new mechanisms for improving bone health, offering hope for more effective treatments in the future. To summarize the diverse and critical roles of the gut microbiome in orthopedic practice, the following table highlights key conditions and their implications for patient care (Table 1). Conclusion: The gut microbiome’s influence on infection, healing, and overall orthopedic outcomes presents an exciting area of exploration. For orthopedic surgeons and clinicians, understanding the gut microbiome’s role offers new preventive and therapeutic pathways, particularly in managing infection risks associated with implants and fractures. Future research may bring even more microbiome-targeted therapies, transforming orthopedic practices and improving patient care in ways that extend beyond traditional approaches. By integrating gut health into orthopedic treatment strategies, health-care providers can foster stronger, more resilient recovery for their patients, advancing the field toward more holistic and effective care.

Predictive Factors for COVID-19 Severity in Patients with Axial Spondyloarthritis: Real-World Data from the Romanian Registry of Rheumatic Diseases

Background and Objectives: Coronavirus disease-2019 (COVID-19) posed unique challenges worldwide, underscoring important gaps in healthcare preparedness for patients receiving immunosuppressive therapies, such as the individuals with axial spondyloarthritis (axSpA), a subgroup of spondyloarthritis (SpA) characterized by chronic inflammation and immune dysregulation. While global registry data exist for SpA, specific data on axSpA alone remain scarce, especially in Central and Eastern European populations. This study aims to identify predictive factors for severe COVID-19 outcomes and provide a descriptive analysis of axSpA patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), using real-world data from the Romanian Registry of Rheumatic Diseases (RRBR). Materials and Methods: This is a three-year retrospective observational cohort study that included 5.786 axSpA patients from the RRBR, of whom 183 (3.16%) were diagnosed with SARS-CoV-2 infection. Data were analyzed using R V4.4.1 and performing univariate and multivariate binary logistic regression to estimate associations using odds ratios (ORs), 95% confidence intervals (CIs), and p-values. A backward selection algorithm was applied to create the final predictive model, accounting for multicollinearity through variance inflation factors (VIFs). Results: The mean age of patients was 48.19 ± 12.26 years, with male predominance (64.5%). Serious COVID-19 (encompassing moderate to critical cases) occurred in 46 cases, with age ≥ 52.5 years (OR 2.64, 95% CI: 1.28-5.48, p = 0.009) and arterial hypertension (OR 2.57, 95% CI: 1.29-5.16, p = 0.007) identified as significant predictors. Individuals with advanced education levels had nearly three times lower odds of experiencing serious COVID-19 (OR 0.38, 95% CI: 0.18-0.76, p = 0.008). Furthermore, our findings confirm the lack of association between HLA-B27 and COVID-19 severity (p = 0.194), contributing to the ongoing discussion regarding its potential immunological role. Moreover, irrespective of the biological therapy administered, the likelihood of experiencing serious SARS-CoV-2 outcomes was not statistically significant (p = 0.882). In the final predictive model, only older age and higher education were deemed as predictive factors. Conclusions: This study highlights key predictors of COVID-19 severity in axSpA patients and emphasizes the protective role of higher education, an underexplored determinant of health outcomes in inflammatory diseases. The lessons learned during these last years can shape a more informed and compassionate healthcare system.

An Actual Insight into the Pathogenic Pathways of Ankylosing Spondylitis

Spondyloarthritis refers to a broad group of conditions that include ankylosing spondylitis, psoriatic arthritis, reactive arthritis, and enteropathic arthritis associated with Crohn's disease or ulcerative colitis. They have been classified by the ASAS group (ASsessment in Ankylosing Spondylitis) into axial spondyloarthritis and peripheral spondyloarthritis. Common features include the absence of autoantibodies, genetic predisposition, and clinical aspects such as axial joint involvement, peripheral manifestations, and extra-articular involvement. However, the pathogenic mechanisms remain complex and incompletely elucidated, despite the fact that the specialized literature has described several pathways that act in synergy: genetic predisposition, environmental factors (infections and mechanical stress), or innate and acquired immune mechanisms. Finally, an inflammatory response is triggered by the recruitment of a large number of inflammatory cells and the release of innate cytokines in the affected areas: joints or periarticular or extraarticular tissues. The current article aims to update and systematize the knowledge accumulated so far on this topic, focusing on the mechanisms that have been involved in the onset, progression, and severity of ankylosing spondylitis.

Identification of novel protein biomarkers and therapeutic targets for ankylosing spondylitis using human circulating plasma proteomics and genome analysis

The proteome serves as the primary basis for identifying targets for treatment. This study conducted proteomic range two-sample Mendelian randomization (MR) analysis to pinpoint potential protein markers and treatment targets for ankylosing spondylitis (AS). A total of 4907 data points on circulating protein expression were collected from a large-scale protein quantitative trait locus investigation involving 35,559 individuals. Using data from a Finnish study on AS as the outcome, the dataset comprised 166,144 individuals of European ancestry (1462 cases and 164,682 controls), and causal relationships were determined through bidirectional Mendelian randomization of two samples. Proteins were further validated and identified through single-cell expression analysis, certain cells showing enriched expression levels were detected, and possible treatment targets were optimized. Increased HERC5 expression predicted by genes was related to increased AS risk, whereas the expression of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, was negatively correlated with AS risk. For each increase in gene-predicted protein levels, the ORs of AS were 2.11 (95% CI 1.44-3.09) for HERC5, 0.14 (95% CI 0.05-0.41) for AIF1, 0.48 (95% CI 0.34-0.68) for CREB3L4, 0.54 (95% CI 0.42-0.68) for MLN, 0.23 (95% CI 0.13-0.38) for MRPL55, and 0.26 (95% CI 0.17-0.39) for SPAG11B. The hypothesis of a reverse causal relationship between these six circulating proteins and AS is not supported. Three of the six protein-coding genes were expressed in both the AS and healthy control groups, while CREB3L4, MLN, and SPAG11B were not detected. Increased levels of HERC5 predicted by genes are related to increased AS risk, whereas the levels of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, negatively correlate with AS risk. HERC5, AIF1, and MRPL55 are potential therapeutic targets for AS. This study advanced the field by employing a novel combination of proteomic range two-sample MR analysis and single-cell expression analysis to identify potential protein markers and therapeutic targets for AS. This approach enabled a comprehensive understanding of the causal relationships between circulating proteins and AS, which has not been extensively explored in previous studies.

Multi-Omics Analysis Unravels the Impact of Stool Sample Logistics on Metabolites and Microbial Composition

Human health and the human microbiome are inevitably intertwined, increasing their relevance in clinical research. However, the collection, transportation and storage of faecal samples may introduce bias due to methodological differences, especially since postal shipping is a common practise in large-scale clinical cohort studies. Using four different Omics layer, we determined the structural (16S rRNA sequencing, cytometric microbiota profiling) and functional integrity (SCFAs, global metabolome) of the microbiota in relation to different easy-to-handle conditions. These conditions were storage at -20 °C, -20 °C as glycerol stock, 4 °C and room temperature with and without oxygen exposure for a maximum of one week. Storage time affected the microbiota on all Omics levels. However, the magnitude was donor-dependent, highlighting the need for purpose-optimized sample collection in clinical multi-donor studies. The effects of oxygen exposure were negligible for all analyses. At ambient temperature, SCFA and compositional profiles were stable for 24 h and 48 h, respectively, while at 4 °C, SCFA profiles were maintained for 48 h. The global metabolome was highly susceptible, already changing at 24 h in non-frozen conditions. Thus, faecal microbiota was best preserved on all levels when transported as a native sample frozen within 24 h, leading to the least biased outcomes in the analysis. We conclude that the immediate freezing of native stool samples for transportation to the lab is best suited for planned multi-Omics analyses that include metabolomics to extend standard sequencing approaches.

Dysregulated Non-Coding RNA Expression in T Cells from Patients with Ankylosing Spondylitis Contributes to Its Immunopathogenesis

Ankylosing spondylitis (AS) is a chronic inflammatory disorder characterized by inflammatory back pain and bony fusion of vertebral joints. Genetic associations and environmental factors have been proposed to explain the immunopathogenesis of AS. In the past few years, there have been major advances in understanding T cell dysfunction in AS. Clinically, targeting interleukin-17A, a major cytokine secreted by T helper 17 cells, has been approved for treating patients with active AS. Non-coding RNAs (ncRNAs) are RNA transcripts that do not translate into proteins. The ncRNAs regulate both innate and adaptive immunity and participate in the pathogenesis of autoimmune diseases, including AS. The main purpose of this article is to review the up-to-date studies investigating the aberrant expression of ncRNAs in T cells from patients with AS and to summarize their roles in its pathogenesis. After searching PubMed for studies published between January 2013 and June 2024, nine studies investigating the expression of ncRNAs in AS T cells were included. We found that aberrantly expressed ncRNAs in AS T cells could cause abnormal cytokine release, cell signaling abnormalities, and dysregulated cell proliferation and death, which contribute to the immunopathogenesis of AS. We discussed some limitations of these studies and suggested several research fields for further investigation.

Effect of Long-Snake Moxibustion on Gut Microbiota of Patients with Ankylosing Spondylitis

OBJECTIVE

The objectively was to study the effect of long-snake moxibustion intervention on gut microbiota of patients with ankylosing spondylitis (AS) by 16S rDNA sequencing technology.

METHODS

Thirty AS patients and 30 healthy volunteers were recruited and treated with long-snake moxibustion once a week for 12 weeks. AS patients were divided into pretreatment and posttreatment groups. VAS, BASDAI, and BASFI scores of AS patients before and after treatment were collected. 16S rDNA high-throughput sequencing technology was used to analyze the characteristics and differences of gut microbiota in AS patients before and after treatment and in healthy volunteers.

RESULTS

VAS, BASDAI, and BASFI scores of AS patients after long-snake moxibustion treatment were lower than those of pretreatment group (p < 0.05). The results of gut microbiota alpha diversity showed that Ace and Chao1 index of the posttreatment group were higher than those of the health group (p < 0.05), but there was no statistical significance in Ace and Chao1 index between the pretreatment group and the posttreatment group (p > 0.05). Beta diversity analysis showed that mild classification aggregation occurred between the health group and the pretreatment group but did not reach a significant level, and there was no significant difference between the pretreatment group and the posttreatment group. The results of species abundance showed that, at the phylum level, compared with the health group, the relative abundance of Firmicutes and Proteobacteria decreased in the pretreatment group, while the relative abundance of Bacteroidetes and Actinobacteria increased. Compared with the pretreatment group, the relative abundance of Firmicutes increased and the relative abundance of Actinobacteria decreased in the posttreatment group, but there were no statistically significant differences in the above changes (p > 0.05). At the genus level, compared with the health group, the relative abundances of Subdoligranulum in the pretreatment group were increased (p < 0.05), while the relative abundances of Bifidobacterium and Streptococcus were decreased (p < 0.05). Compared with the pretreatment group, the relative abundance of Romboutsia in the posttreatment group was increased (p < 0.05).

CONCLUSION

Long-snake moxibustion can obviously improve the clinical symptoms of AS patients. The possible mechanism of action is related to regulating the abundance of gut microbiota, increasing beneficial bacteria, and restoring the homeostasis of gut microorganisms.

Causal relationship between gut microbiota and ankylosing spondylitis and potential mediating role of inflammatory cytokines: A mendelian randomization study

Associations between gut microbiota and ankylosing spondylitis have been discovered in previous studies, but whether these associations reflect a causal relationship remains inconclusive. Aiming to reveal the bidirectional causal associations between gut microbiota and ankylosing spondylitis, we utilized publicly available genome wide association study summary data for 211 gut microbiota (GM) taxa and ankylosing spondylitis (AS) to conduct two sample mendelian randomization analyses. Mediation analysis was performed to explore mediating inflammatory cytokines. We found that genetically predicted higher abundance of Lactobacillaceae family, Rikenellaceae family and Howardella genus had suggestive associations with decreased risk of ankylosing spondylitis while genetic proxied higher abundance of Actinobacteria class and Ruminococcaceae_NK4A214_group genus was associated with increased risk of ankylosing spondylitis. IL23 and IFN-γ were potential mediating cytokines for GM dysbiosis, especially for Actinobacteria class, leading to AS. Our study provided a new exploration direction for the treatment of AS. Lactobacillaceae family, Rikenellaceae family, Howardella genus, Actinobacteria class and Ruminococcaceae_NK4A214_group genus are expected to become new therapeutic targets and monitoring indicators for AS.

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.

Gut microbiota in axial spondyloarthritis : genetics, medications and future treatments

Axial spondyloarthritis, also referred to as ankylosing spondylitis, is a chronic inflammatory condition that predominantly affects the axial spine but may also present with peripheral arthritis. It falls within the umbrella of disorders known as spondyloarthropathies. In addition to axial spondyloarthritis, this group includes psoriatic arthritis, enteropathic arthritis, reactive arthritis, and undifferentiated spondyloarthropathy, with axial spondyloarthritis being one of the most common. The overall mechanisms underlying the development of axial spondyloarthritis are complex and multifactorial. There is a significant and well-recognized association between axial spondyloarthritis and the HLA-B27 gene, but there have also been non-HLA genes identified in the disease process, as well as certain inflammatory cytokines that play a role in the inflammatory process, such as tumor necrosis factor (TNF). More recently, there has been research and new evidence linking changes in the gut microbiota to the disease process of axial spondyloarthritis. Research into the role of the gut microbiota and gut dysbiosis is a large, ever-growing field. It has been associated with a multitude of conditions, including axial spondyloarthritis. This mini-review highlights the symbiotic relationship of the gut microbiota with the pathogenesis, therapeutic agents and future treatments of axial spondyloarthritis.

Combined analysis of metabolomics and 16S rRNA sequencing for ankylosing spondylitis patients before and after secukinumab therapy

OBJECTIVE

Alterations in gut microbiota have been implicated in the pathogenesis of ankylosing spondylitis (AS), but the underlying mechanisms remain elusive. This study aims to investigate changes in gut microbiota and metabolites in individuals with AS before and after treatment with secukinumab, to identify the biological characteristics specific to AS patients and investigate the potential biomarkers, for optimizing therapeutic strategies more effectively.

METHODS

Fecal microbiome data were collected from 30 AS patients before and after secukinumab therapy and compared with data from 40 healthy controls (HC). Additionally, we analyzed the metabolic profile of both groups from plasma.

RESULTS

Findings indicated that the treatment-induced changes in the composition of several crucial bacterial groups, including Megamonas, Prevotella_9, Faecalibacterium, Roseburia, Bacteroides, and Agathobacter. Post-treatment, these groups exhibited a distribution more akin to that of the healthy populations compared with their pretreatment status. We identified three gut microbial taxa, namely Prevotellaceae_bacterium_Marseille_P2831, Prevotella_buccae, and Elusimicrobiota, as potential biomarkers for diagnosing individuals at a higher risk of developing AS and assessing disease outcomes. Plasma metabolomics analysis revealed 479 distinct metabolites and highlighted three disrupted metabolic pathways. Integration of microbiome and metabolomics datasets demonstrated a significant degree of correlation, underscoring the impact of the microbiome on metabolic activity.

CONCLUSION

Secukinumab can restore the balance of the gut microbiome and metabolites in AS patients, rendering them more similar to those found in the healthy population. The analysis of microbiome and metabolomics data have unveiled some candidate biomarkers capable of evaluating treatment efficacy.

Association between gut microbiota and spinal stenosis: a two-sample mendelian randomization study

Introduction

Considerable evidence has unveiled a potential correlation between gut microbiota and spinal degenerative diseases. However, only limited studies have reported the direct association between gut microbiota and spinal stenosis. Hence, in this study, we aimed to clarify this relationship using a two-sample mendelian randomization (MR) approach.

Materials and Methods

Data for two-sample MR studies was collected and summarized from genome-wide association studies (GWAS) of gut microbiota (MiBioGen, n = 13, 266) and spinal stenosis (FinnGen Biobank, 9, 169 cases and 164, 682 controls). The inverse variance-weighted meta-analysis (IVW), complemented with weighted median, MR-Egger, weighted mode, and simple mode, was used to elucidate the causality between gut microbiota and spinal stenosis. In addition, we employed mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and the MR-Egger intercept test to assess horizontal multiplicity. Cochran's Q test to evaluate heterogeneity, and "leave-one-out" sensitivity analysis to determine the reliability of causality. Finally, an inverse MR analysis was performed to assess the reverse causality.

Results

The IVW results indicated that two gut microbial taxa, the genus Eubacterium fissicatena group and the genus Oxalobacter, have a potential causal relationship with spinal stenosis. Moreover, eight potential associations between genetic liability of the gut microbiota and spinal stenosis were implied. No significant heterogeneity of instrumental variables or horizontal pleiotropy were detected. In addition, "leave-one-out" sensitivity analysis confirmed the reliability of causality. Finally, the reverse MR analysis revealed that no proof to substantiate the discernible causative relationship between spinal stenosis and gut microbiota.

Conclusion

This analysis demonstrated a possible causal relationship between certain particular gut microbiota and the occurrence of spinal stenosis. Further studies focused on the mechanism of gut microbiota-mediated spinal stenosis can lay the groundwork for targeted prevention, monitoring, and treatment of spinal stenosis.

6-formylindolo[3, 2-b]carbazole alters gut microbiota and prevents the progression of ankylosing spondylitis in mice

Ankylosing spondylitis (AS), is known as a chronic inflammatory autoimmune disease, there is evidence to suggest that gut microbiota disorders may be related to the occurrence and development of AS. Studies have shown that 6-formylindolo[3, 2-b]carbazole (FICZ) has the ability to modulate intestinal homeostasis and inhibit inflammatory responses. The purpose of this work is to evaluate the protective role of FICZ in treating AS and elucidate potential mechanisms. FICZ was administered to the proteoglycan (PG)-induced AS mice for 7 consecutive weeks. The effects of FICZ on AS mice were evaluated by the disease severity, intestinal histopathology, proinflammatory cytokine levels, and intestinal mucosal barrier function. The gut microbiota compositions were profiled through 16S rDNA high-throughput sequencing. We found that FICZ significantly reduced the severity of AS and resulted in the downregulating of TNF-α and IL-17A inflammatory cytokines. Moreover, FICZ ameliorated pathological changes in the ileal and improved intestinal mucosal barrier function. Furthermore, FICZ altered the composition of the gut microbiota by increasing the Bacteroidetes/Firmicutes phylum ratio and enriched the genes related to "glycan biosynthesis and metabolism", thus reversing the process of AS. In conclusion, FICZ suppressed the progression of AS and altered gut microbiota in AS mice, which provided new insight into AS therapy strategy.

Clinical features and fecal microbiota characteristics of patients with both ulcerative colitis and axial spondyloarthritis

BACKGROUND

The role of the intestinal microbiota in the pathogenesis of inflammatory bowel disease combined with axial spondyloarthritis (axSpA) is gaining widespread interest.

AIMS

This study was conducted to investigate the clinical and fecal microbiota characteristics of patients with both ulcerative colitis (UC) and axSpA.

METHODS

Clinical data were collected from patients with UC. Patients were divided into the axSpA and non-axSpA groups according to human leukocyte antigen-B27 serology and sacroiliac joint imaging results. We obtained fecal specimens from 14 axSpA and 26 non-axSpA patients. All samples underwent 16S ribosomal DNA sequencing.

RESULTS

Seventy-three patients with UC were included in this study, and the axSpA incidence was 19.2%. This incidence was significantly higher in patients with C-reactive protein > 10 mg/L. Firmicutes and Faecalibacterium abundances were decreased, and Proteobacteria and Escherichia_Shigella abundances were increased in the axSpA group compared with those of the non-axSpA group. Indicator analysis showed that Escherichia_Shigella was more likely to be an indicator species of axSpA. Additionally, many biosynthetic and metabolic pathways, including glutathione metabolism, fatty acid degradation, geraniol degradation, and biosynthesis of siderophore group nonribosomal peptides, were upregulated in the axSpA group.

CONCLUSION

Patients with UC have a high axSpA incidence, which may be related to the relative abundances of Escherichia_Shigella in these patients. The abundances of various biosynthetic and metabolic pathways of the fecal flora were upregulated in patients with axSpA.

Dry and wet experiments reveal diagnostic clustering and immune landscapes of cuproptosis patterns in patients with ankylosing spondylitis

Cuproptosis is a new manner of mitochondrial cell death induced by copper. There is evidence that serum copper has a crucial impact on ankylosing spondylitis (AS) by copper-induced inflammatory response. However, the molecular mechanisms of cuproptosis modulators in AS remain unknown. We aimed to use a bioinformatics-based method to comprehensively investigate cuproptosis-related subtype identification and immune microenvironment infiltration of AS. Additionally, we further verified the results by in vitro experiments, in which peripheral blood and fibroblast cells from AS patients were used to evaluate the functions of significant cuproptosis modulators on AS. Finally, eight significant cuproptosis modulators were identified by analysis of differences between controls and AS cases from GSE73754 dataset. Eight prognostic cuproptosis modulators (LIPT1, DLD, PDHA1, PDHB, SLC31A1, ATP7A, MTF1, CDKN2A) were identified using a random forest model for prediction of AS risk. A nomogram model of the 8 prognostic cuproptosis modulators was then constructed; the model could be beneficial in clinical settings, as indicated by decision curve analysis. Consensus clustering analysis was used to divide AS patients into two cuproptosis subtypes (clusterA & B) according to significant cuproptosis modulators. The cuproptosis score of each sample was calculated by principal component analysis to quantify cuproptosis subtypes. The cuproptosis scores were higher in clusterB than in clusterA. Additionally, cases in clusterA were closely associated with the immunity of activated B cells, Activated CD4 T cell, Type17 T helper cell and Type2 T helper cell, while cases in clusterB were linked to Mast cell, Neutrophil, Plasmacytoid dendritic cell immunity, indicating that clusterB may be more correlated with AS. Notably, key cuproptosis genes including ATP7A, MTF1, SLC31A1 detected by RT-qPCR with peripheral blood exhibited significantly higher expression levels in AS cases than controls; LIPT1 showed the opposite results; High MTF1 expression is correlated with increased osteogenic capacity. In general, this study of cuproptosis patterns may provide promising biomarkers and immunotherapeutic strategies for future AS treatment.

Association between type 1 diabetes mellitus and ankylosing spondylitis: a two-sample Mendelian randomization study

Objective

The development of ankylosing spondylitis (AS) is closely related to autoimmune system dysfunction. Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is a risk factor for many diseases. This study aimed to investigate the causal relationship between T1DM mellitus and AS genetically.

Methods

A genome-wide association study (GWAS) of causal relationships between exposure (T1DM) and outcome (AS) was performed using summary data from the GWAS database. We conducted a two-sample Mendelian randomization (MR) study of these two diseases. Inverse variance weighting (IVW) was used as the primary analysis method, with MR Egger, weighted median, and weighted mode used as supplementary methods. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-Pleiotropy RESidual Sum and outlier methods, leave-one-out analysis, and funnel plots.

Results

A total of 11 single nucleotide polymorphisms (SNPs)were identified for instrumental variables(IVs) for MR analysis.IVW found that T1DM was causally associated with AS ((IVW: OR = 1.0006 (95% CI 1.0001, 1.0011), p = 0.0057; MR-Egger: OR = 1.0003 (95% CI 0.9995, 1.0012), p = 0.4147; weighted median: OR = 1.0006 (95% CI 1.0003, 1.0008), p = 0.0001; weighted mode: OR = 1.0007 (95% CI 1.0005, 1.0009), p = 0.0001). No horizontal pleiotropy was found for the MR-Egger intercept, and leave -one-out analysis found that the results remained stable after the removal of individual SNPs.

Conclusion

The results of the two-sample MR analysis supported a causal relationship between T1DM and AS risk.

Beyond the horizon: Innovations and future directions in axial-spondyloarthritis

Axial spondyloarthritis (axSpA) is a chronic inflammatory disease of the spine and sacroiliac joints. This review discusses recent advances across multiple scientific fields that promise to transform axSpA management. Traditionally, axSpA was considered an immune-mediated disease driven by human leukocyte antigen B27 (HLA-B27), interleukin (IL)-23/IL-17 signaling, biomechanics, and dysbiosis. Diagnosis relies on clinical features, laboratory tests, and imaging, particularly magnetic resonance imaging (MRI) nowadays. Management includes exercise, lifestyle changes, non-steroidal anti-inflammatory drugs and if this is not sufficient to achieve disease control also biological and targeted-synthetic disease modifying anti-rheumatic drugs. Beyond long-recognized genetic risks like HLA-B27, high-throughput sequencing has revealed intricate gene-environment interactions influencing dysbiosis, immune dysfunction, and aberrant bone remodeling. Elucidating these mechanisms promises screening approaches to enable early intervention. Advanced imaging is revolutionizing the assessment of axSpA's hallmark: sacroiliac bone-marrow edema indicating inflammation. Novel magnetic resonance imaging (MRI) techniques sensitively quantify disease activity, while machine learning automates complex analysis to improve diagnostic accuracy and monitoring. Hybrid imaging like synthetic MRI/computed tomography (CT) visualizes structural damage with new clarity. Meanwhile, microbiome analysis has uncovered gut ecosystem alterations that may initiate joint inflammation through HLA-B27 misfolding or immune subversion. Correcting dysbiosis represents an enticing treatment target. Moving forward, emerging techniques must augment patient care. Incorporating patient perspectives will be key to ensure innovations like genetics, microbiome, and imaging biomarkers translate into improved mobility, reduced pain, and increased quality of life. By integrating cutting-edge, multidisciplinary science with patients' lived experience, researchers can unlock the full potential of new technologies to deliver transformative outcomes. The future is bright for precision diagnosis, tightly controlled treatment, and even prevention of axSpA.

The causality between gut microbiota and ankylosing spondylitis: Insights from a bidirectional two-sample Mendelian randomization analysis

BACKGROUND

The association between gut microbiota and ankylosing spondylitis (AS) has been reported in the literature; however, whether the two are correlative is unclear.

METHODS

Single nucleotide polymorphisms associated with the gut microbiome composition and AS (968 AS cases and 336 191 controls) were obtained from published genome-wide association studies in this two-sample Mendelian randomization (MR) study. The causal relationship between gut microbiota and AS was estimated using the inverse-variance weighted method, and the robustness of our findings was confirmed through a comprehensive series of sensitivity analyses.

RESULTS

Anaerotruncus (OR = 0.9984, 95% CI, 0.9968-0.9999, p = .0405) and Ruminococcaceae UCG002 (OR = 0.9989, 95% CI, 0.9979-0.9999, p = .0375) were protective against AS. Defluviitaleaceae (OR = 1.0015, 95% CI, 1.0005-1.0025, p = .0048), Butyricicoccus (OR = 1.0016, 95% CI, 1.0001-1.0032, p = .0429), Coprococcus 3 (OR = 1.0016, 95% CI, 1.0000-1.0032, p = .0463), and Defluviitaleaceae UCG011 (OR = 1.0016, 95% CI, 1.0005-1.0027, p = .0041) exhibited significant positive correlations with heightened susceptibility to AS. Reverse MR revealed that AS does not affect the gut microbial composition.

CONCLUSION

Our study has established a genetically-based causal relationship between gut microbiota and AS. This finding suggests that we may be able to target and regulate specific bacterial groups in the gut to prevent and treat AS.

Gut microbiota and thyroid-associated ophthalmopathy

Thyroid-associated ophthalmopathy (TAO) is a multifactorial-mediated autoimmune orbital disease with the highest incidence of orbital disease in adults. Due to the complex clinical manifestations and prolonged course,TAO seriously affect the physical and mental health of patients.The pathogenesis of TAO has not been fully elucidated and the treatment lacks specificity. Therefore, in-depth research on the pathogenesis of TAO is to find effective treatments. In recent years, studies have suggested that there is gut microbiota disorder in TAO, and the risk factors of TAO can promote gut microbiota disorder. Disordered gut microbiota can participate in the occurrence and development of TAO via influencing T cell differentiation, mimicking autoantigens, and influencing host non-coding RNA expression. Modulating the gut microbiota also has therapeutic effects on TAO and is a promising therapeutic approach.

Small Intestinal Permeability and Metabolomic Profiles in Feces and Plasma Associate With Clinical Response in Patients With Active Psoriatic Arthritis Participating in a Fecal Microbiota Transplantation Trial: Exploratory Findings From the FLORA Trial

OBJECTIVE

We investigated intestinal permeability and fecal, plasma, and urine metabolomic profiles in methotrexate-treated active psoriatic arthritis (PsA) and how this related to clinical response following one sham or fecal microbiota transplantation (FMT).

METHODS

This exploratory study is based on the FLORA trial cohort, in which 31 patients with moderate-to-high peripheral PsA disease activity, despite at least 3 months of methotrexate-treatment, were included in a 26-week, double-blind, 1:1 randomized, sham-controlled trial. Participants were randomly allocated to receive either one healthy donor FMT (n = 15) or sham (n = 16) via gastroscopy. The primary trial end point was the proportion of treatment failures through 26 weeks. We performed a lactulose-to-mannitol ratio (LMR) test at baseline (n = 31) and at week 26 (n = 26) to assess small intestinal permeability. Metabolomic profiles in fecal, plasma, and urine samples collected at baseline, weeks 4, 12, and 26 were measured using 1 H Nuclear Magnetic Resonance.

RESULTS

Trial failures (n = 7) had significantly higher LMR compared with responders (n = 19) at week 26 (0.027 [0.017-0.33]) vs. 0.012 [0-0.064], P = 0.013), indicating increased intestinal permeability. Multivariate analysis revealed a significant model for responders (n = 19) versus failures (n = 12) at all time points based on their fecal (P < 0.0001) and plasma (P = 0.005) metabolomic profiles, whereas urine metabolomic profiles did not differ between groups (P = 1). Fecal N-acetyl glycoprotein GlycA correlated with Health Assessment Questionnaire Disability Index (coefficient = 0.50; P = 0.03) and fecal propionate correlated with American College of Rheumatology 20 response at week 26 (coefficient = 27, P = 0.02).

CONCLUSION

Intestinal permeability and fecal and plasma metabolomic profiles of patients with PsA were associated with the primary clinical trial end point, failure versus responder.

Ankylosing spondylitis and psychiatric disorders in European population: a Mendelian randomization study

Background

Epidemiologic evidence has demonstrated a correlation between ankylosing spondylitis and psychiatric disorders. However, little is known about the common genetics and causality of this association. This study aimed to investigate the common genetics and causality between ankylosing spondylitis (AS) and psychiatric disorders.

Methods

A two-sample Mendelian Randomization (MR) analysis was carried out to confirm causal relationships between ankylosing spondylitis and five mental health conditions including major depressive disorder (MDD), anxiety disorder (AXD), schizophrenia (SCZ), bipolar disorder (BIP), and anorexia nervosa (AN). Genetic instrumental variables associated with exposures and outcomes were derived from the largest available summary statistics of genome-wide association studies (GWAS). Bidirectional causal estimation of MR was primarily obtained using the inverse variance weighting (IVW) method. Other MR methods include MR-Egger regression, Weighted Median Estimator (WME), Weighted Mode, Simple Mode, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO). Sensitivity analyses are conducted to estimate the robustness of MR results.

Results

The findings suggest that AS may be causally responsible for the risk of developing SCZ (OR = 1.18, 95% confidence interval = (1.06, 1.31), P = 2.58 × 10-3) and AN (OR = 1.32, 95% confidence interval = (1.07, 1.64), P = 9.43 × 10-3). In addition, MDD, AXD, SCZ, AN, and BIP were not inversely causally related to AS (all p > 0.05).

Conclusion

Our study provides fresh insights into the relationship between AS and psychiatric disorders (SCZ and AN). Furthermore, it may provide new clues for risk management and preventive interventions for mental disorders in patients with AS.

Updates on ankylosing spondylitis: pathogenesis and therapeutic agents

Ankylosing spondylitis (AS) is an autoinflammatory disease that manifests with the unique feature of enthesitis. Gut microbiota, HLA-B*27, and biomechanical stress mutually influence and interact resulting in setting off a flame of inflammation. In the HLA-B*27 positive group, dysbiosis in the gut environment disrupts the barrier to exogenous bacteria or viruses. Additionally, biomechanical stress induces inflammation through enthesial resident or gut-origin immune cells. On this basis, innate and adaptive immunity can propagate inflammation and lead to chronic disease. Finally, bone homeostasis is regulated by cytokines, by which the inflamed region is substituted into new bone. Agents that block cytokines are constantly being developed to provide diverse therapeutic options for preventing the progression of inflammation. In addition, some antibodies have been shown to distinguish disease selectively, which support the involvement of autoimmune immunity in AS. In this review, we critically analyze the complexity and uniqueness of the pathogenesis with updates on the findings of immunity and provide new information about biologics and biomarkers.

Pathophysiology and immunolgical basis of axial spondyloarthritis

Over the recent years the wider availability and application of state-of-the-art immunological technologies greatly advanced the insight into the mechanisms that play an important role in axial spondyloarthritis (axSpA) pathophysiology. This increased understanding has facilitated the development of novel treatments that target disease relevant pathways, hereby improving outcome for axSpA patients. In axSpA pathophysiology genetic and environmental factors as well as immune activation by mechanical or bacterial stress resulting in a chronic inflammatory response have a central role. The TNF and IL-23/IL-17 immune pathways play a pivotal role in these disease mechanisms. This review provides an outline of the immunological basis of axSpA with a focus on key genetic risk factors and their link to activation of the pathological immune response, as well as on the role of the gut and entheses in the initiation of inflammation with subsequent new bone formation in axSpA.

Alterations in the gut virome in patients with ankylosing spondylitis

Introduction

Ankylosing spondylitis (AS), a chronic autoimmune disease, has been linked to the gut bacteriome.

Methods

To investigate the characteristics of the gut virome in AS, we profiled the gut viral community of 193 AS patients and 59 healthy subjects based on a metagenome-wide analysis of fecal metagenomes from two publicly available datasets.

Results

AS patients revealed a significant decrease in gut viral richness and a considerable alteration of the overall viral structure. At the family level, AS patients had an increased abundance of Gratiaviridae and Quimbyviridae and a decreased abundance of Drexlerviridae and Schitoviridae. We identified 1,004 differentially abundant viral operational taxonomic units (vOTUs) between patients and controls, including a higher proportion of AS-enriched Myoviridae viruses and control-enriched Siphoviridae viruses. Moreover, the AS-enriched vOTUs were more likely to infect bacteria such as Flavonifractor, Achromobacter, and Eggerthellaceae, whereas the control-enriched vOTUs were more likely to be Blautia, Ruminococcus, Collinsella, Prevotella, and Faecalibacterium bacteriophages. Additionally, some viral functional orthologs differed significantly in frequency between the AS-enriched and control-enriched vOTUs, suggesting the functional role of these AS-associated viruses. Moreover, we trained classification models based on gut viral signatures to discriminate AS patients from healthy controls, with an optimal area under the receiver operator characteristic curve (AUC) up to 0.936, suggesting the clinical potential of the gut virome for diagnosing AS.

Discussion

This work provides novel insight into the AS gut virome, and the findings may guide future mechanistic and therapeutic studies for other autoimmune diseases.

Dietary Fiber Intake Influences Changes in Ankylosing Spondylitis Disease Status

The objectives of this study were to characterize dietary fiber (DF) intake in patients with ankylosing spondylitis (AS), to assess whether DF intake affects disease activity in AS, and to investigate the effect of DF intake on disease activity in AS in the context of functional bowel disease (FBD) symptoms. We recruited 165 patients with AS and divided them into two groups according to whether they had a high DF intake > 25 g/d to investigate the characteristics of people with high DF intake. Some 72 of the 165 AS patients (43%) met the criteria for high DF intake, which was more common in patients with negative FBD symptoms (68%). Data analysis revealed that DF intake was negatively associated with AS disease activity and did not differ statistically significantly from FBD symptoms. Multivariate adjusted models were used to explore the effect of DF intake on AS disease activity. ASDAS-CRP and BASDAI were stable and negatively correlated across models in both groups with and without FBD symptoms. Thus, DF intake positively affected disease activity in patients with AS. ASDAS-CRP and BASDAI were negatively correlated with DF intake.

Peptidomics analysis of plasma in patients with ankylosing spondylitis

Background

This study aimed to explore the differential expression of peptides associated with ankylosing spondylitis (AS) patients, enabling identification of potential functional peptides to provide the basis for the novel intervention targets for AS.

Material and Methods

3 AS patients and 3 healthy volunteers were enrolled in this study. The expression profiles for peptides present in the plasma of AS patients and the healthy individual were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The physicochemical properties and biological functions of identified peptides were further analyzed by bioinformatics. The results of peptide identification were verified by cell viability analysis, using CCK8 and Edu staining assay, and the differential peptides relevant to the disease were screened.

Results

52 differential peptides were successfully identified using mass spectrometry. 44 peptides were up-regulated, while eight were down-regulated. FGA-peptide (sequences: DSGEGDFLAEGGGVRGPR), C4A-peptide (sequences: NGFKSHAL), and TUBB-peptide (sequences: ISEQFTAMFR) were screened out that could significantly promote the proliferation of fibroblasts in AS patients. Bioinformatics analysis showed these differentially expressed peptides might be associated with "MHC class I protein binding" and "pathogenic Escherichia coli infection" pathways, which might further affect the progression of AS.

Conclusion

This pilot study shows 3 differentially expressed peptides may have the potential function for the occurrence and development of AS, may provide novel insights into the underlying molecular mechanisms of AS based on peptide omics.