The change of plasma metabolic profile and gut microbiome dysbiosis in patients with rheumatoid arthritis

A preliminary study of serum metabolomic profiling in male patients with acute brucellosis

Brucellosis is a significant zoonotic disease that may lead to metabolic profile changes, which remain insufficiently studied. This study utilized an ultra-high performance liquid chromatography coupled with Q Exactive-Orbitrap mass spectrometry (UHPLC-QExactive-Orbitrap MS/MS) to investigate serum samples of acute brucellosis in 32 male patients against 32 well-matched healthy controls. The results revealed nine differential metabolites that correlated with human acute brucellosis, all showing increased levels, except cis-4-hydroxy-D-proline, inosine, hypoxanthine and azelaic acid. These differential metabolites were predominantly involved in metabolic pathways, such as primary bile acid biosynthesis, purine metabolism, taurine and hypotaurine metabolism, and d-amino acid metabolism. This study identified potential metabolite biomarkers of acute brucellosis and laid the foundation for its early diagnosis and prognostic assessment, thus helping to prevent the chronicity of acute brucellosis.

Animal Models Informing the Role of the Microbiome and its Metabolites in Rheumatoid Arthritis

Animal models of rheumatoid arthritis (RA) are essential for understanding the disease's mechanisms and developing new treatments. Recent research highlights the microbiome's significant roles in RA pathogenesis, influencing disease susceptibility and progression. These models allow researchers to investigate the causal relationships between specific microbial species and arthritis development. Despite challenges in translating findings to human conditions, animal models are crucial for uncovering microbiome-related therapeutic strategies, advancing our understanding of RA, and improving patient outcomes.

Linking microbial communities to rheumatoid arthritis: focus on gut, oral microbiome and their extracellular vesicles

Rheumatoid arthritis (RA) is a severe, chronic autoimmune disease affecting approximately 1% of the global population. Research has demonstrated that microorganisms play a crucial role in the onset and progression of RA. This indicates that the disruption of immune homeostasis may originate from mucosal sites, such as the gut and oral cavity. In the intestines of patients in the preclinical stage of RA, an increased abundance of Prevotella species with a strong association to the disease was observed. In the oral cavity, infections by Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans can mediate the production of anti-citrullinated protein antibodies (ACPAs), potentially contributing to RA pathogenesis. Nevertheless, no single bacterial species has been consistently identified as the primary driver of RA. This review will discuss the connection between gut and oral bacteria in the development of arthritis. Additionally, it explores the role of bacterial extracellular vesicles (bEVs) in inducing inflammation and their potential pathogenic roles in RA.

Role of Gut Microbiota in the Development of Some Autoimmune Diseases

The gut microbiota is crucial for maintaining the homeostasis and function of the immune system. It interacts with the host's immune system through various mechanisms, including promoting immune tolerance, affecting the differentiation and function of immune cells, and participating in the metabolism of immune regulatory substances. The disruption of the gut microbiome may lead to impaired mucosal barrier function, allowing bacteria and their metabolites to invade into the host, activate or interfere with the immune system, and potentially trigger or exacerbate autoimmune responses. Understanding the relationship between the microbiome and autoimmune diseases may help develop new treatment strategies. This article reviewed the recent progresses of microbiome involved in the occurrence and development of some autoimmune diseases and the treatment methods based on regulation of the microbiome, highlighted the key role of microbiome in autoimmune diseases.

The Causal Relationship Between Genetically Determined Plasma Metabolites and Rheumatoid Arthritis

BACKGROUND

Presently, research examining the impact of plasma metabolites on rheumatoid arthritis (RA) is scarce. We utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the potential causal link between 1400 plasma metabolites and RA.

METHODS

We performed a two-sample MR analysis to assess the causal association between 1400 plasma metabolites and RA. The primary method of two-sample MR Analysis was the Inverse Variance Weighted (IVW) model, and the secondary methods were the Weighted Median (WM) and MR Egger methods. We conducted sensitivity analyses using Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. Steiger test was used for validation of the metabolites. The main results were validated in the UK Biobank.

RESULTS

In the discovery dataset, 60 metabolites were identified as significantly associated with the onset of RA. A notable finding was the strong correlation between Valve levels and RA risk, showing the highest positive correlation (OR [95% CI]: 1.361 (1.112, 1.667), p = 0.0028). Subsequent analysis of the validation dataset revealed 46 metabolites linked to RA, with X-22771 levels displaying the strongest positive association (OR [95% CI]: 1.002 (1.00, 1.004), p = 0.037). Notably, Glycohydrocolate levels exhibited a protective effect on RA in both datasets. Specifically, the effect size in the initial dataset was (OR [95% CI]:0.867 (0.753, 1.000), p = 0.050), whereas in the validation dataset, the effect was weaker (OR [95% CI]: 0.999 (0.997, 1.000), p = 0.048). These findings were further validated through a series of sensitivity analyses, affirming their robustness and reliability.

CONCLUSIONS

This study highlights a strong correlation between elevated Valine levels and an increased risk of RA, as well as potential protective effects of Glycohydrohorate in independent datasets.

Integrated multi-omics revealed that dysregulated lipid metabolism played an important role in RA patients with metabolic diseases

OBJECTIVES

Patients with rheumatoid arthritis (RA) commonly experience a high prevalence of multiple metabolic diseases (MD), leading to higher morbidity and premature mortality. Here, we aimed to investigate the pathogenesis of MD in RA patients (RA_MD) through an integrated multi-omics approach.

METHODS

Fecal and blood samples were collected from a total of 181 subjects in this study for multi-omics analyses, including 16S rRNA and internally transcribed spacer (ITS) gene sequencing, metabolomics, transcriptomics, proteomics and phosphoproteomics. Spearman's correlation and protein-protein interaction networks were used to assess the multi-omics data correlations. The Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithm were used to identify disease-specific biomarkers for RA_MD diagnosis.

RESULTS

Our results found that RA_MD was associated with differential abundance of gut microbiota such as Turicibacter and Neocosmospora, metabolites including decreased unsaturated fatty acid, genes related to linoleic acid metabolism and arachidonic acid metabolism, as well as downregulation of proteins and phosphoproteins involved in cholesterol metabolism. Furthermore, a multi-omics classifier differentiated RA_MD from RA with high accuracy (AUC: 0.958). Compared to gouty arthritis and systemic lupus erythematosus, dysregulation of lipid metabolism showed disease-specificity in RA_MD.

CONCLUSIONS

The integration of multi-omics data demonstrates that lipid metabolic pathways play a crucial role in RA_MD, providing the basis and direction for the prevention and early diagnosis of MD, as well as new insights to complement clinical treatment options.

Mendelian randomization identifies causal associations between GWAS-associated bacteria and their metabolites and rheumatoid arthritis

Background

Accumulating evidence suggests that an imbalance of gut microbiota is commonly observed in patients with rheumatoid arthritis (RA). However, it remains unclear whether gut microbiota dysbiosis is a cause or consequence of RA, and the mechanisms by which gut dysbiosis contributes to RA have not been fully understood. This study aimed to investigate the causal relationship between gut microbiota and metabolites with RA.

Methods

A two-sample Mendelian randomization analysis was performed to estimate the causality of gut microbiota and metabolites on RA. A genome-wide association study (GWAS) of 211 gut microbiota and 217 metabolites was used as the exposure, whereas RA was treated as the outcome. Inverse variance weighted (IVW) was regarded as the primary approach for calculating causal estimates. MR Egger method, Weighted median method, Simple mode method, and weighted mode method were used for sensitive analysis. Metabolic pathway analysis was performed via the web-based Metaconflict 5.0. Additionally, an animal study was undertaken to evaluate the results inferred by Mendelian randomization.

Result

This study indicated that six gut microbiota taxa (RuminococcaceaeUCG013, Erysipelotrichia, Erysipelotrichaceae, Erysipelotrichales, Clostridia, and Veillonellaceae) were estimated to exert a positive impact on RA. Conversely, seven gut microbiota taxa (Oxalobacter, Cyanobacteria, RuminococcaceaeUCG002, LachnospiraceaeUCG010, Christensenellaceae, Oxalobacteraceae, Anaerostipes) were estimated to exert a negative impact on RA. Three metabolites, namely indole-3-propionate (IPA), glycine and sphingomyelin (SM 16:1), were found to be linked to lower RA risk, while five metabolites (argininosuccinate, CE 20_4, TAG 58_8, PC 40_6, and LPC 20_4) were linked to higher RA risk. Additionally, four metabolic pathways were identified by metabolic pathway analysis. The collagen-induced arthritis (CIA) rats exhibited a higher relative abundance of Class_Clostridia and a lower abundance of Genus_Lachnospiraceae (p < 0.05) than the healthy controls.

Conclusion

This study identified causal associations between specific gut microbiota, metabolites, and RA. These findings support the significant role of gut microbiota and metabolites in RA pathogenesis.

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.

Inflammation and Organic Cation Transporters Novel (OCTNs)

Inflammation is a physiological condition characterized by a complex interplay between different cells handled by metabolites and specific inflammatory-related molecules. In some pathological situations, inflammation persists underlying and worsening the pathological state. Over the years, two membrane transporters namely OCTN1 (SLC22A4) and OCTN2 (SLC22A5) have been shown to play specific roles in inflammation. These transporters form the OCTN subfamily within the larger SLC22 family. The link between these proteins and inflammation has been proposed based on their link to some chronic inflammatory diseases such as asthma, Crohn's disease (CD), and rheumatoid arthritis (RA). Moreover, the two transporters show the ability to mediate the transport of several compounds including carnitine, carnitine derivatives, acetylcholine, ergothioneine, and gut microbiota by-products, which have been specifically associated with inflammation for their anti- or proinflammatory action. Therefore, the absorption and distribution of these molecules rely on the presence of OCTN1 and OCTN2, whose expression is modulated by inflammatory cytokines and transcription factors typically activated by inflammation. In the present review, we wish to provide a state of the art on OCTN1 and OCTN2 transport function and regulation in relationships with inflammation and inflammatory diseases focusing on the metabolic signature collected in different body districts and gene polymorphisms related to inflammatory diseases.

Association Between Human Metabolomics and Rheumatoid Arthritis: A Systematic Review and Meta-analysis

OBJECTIVE

The underdiagnosis and inadequate treatment of rheumatoid arthritis (RA) can be attributed to the various clinical manifestations presented by patients. To address this concern, we conducted an extensive review and meta-analysis, focusing on RA-related metabolites.

METHODS

A comprehensive literature search was conducted in PubMed, the Cochrane Library, Web of Science, and Embase to identify relevant studies published up to October 5, 2022. The quality of the included articles was evaluated and, subsequently, a meta-analysis was conducted using Review Manager software to analyze the association between metabolites and RA.

RESULTS

Forty nine studies met the inclusion criteria for the systematic review, and six of these studies were meta-analyzed to evaluate the association between 28 reproducible metabolites and RA. The results indicated that, compared to controls, the levels of histidine (RoM = 0.83, 95% CI = 0.79-0.88, I2 = 0%), asparagine (RoM = 0.83, 95% CI = 0.75-0.91, I2 = 0%), methionine (RoM = 0.82, 95% CI = 0.69-0.98, I2 = 85%), and glycine (RoM = 0.81, 95% CI = 0.67-0.97, I2 = 68%) were significantly lower in RA patients, while hypoxanthine levels (RoM = 1.14, 95% CI = 1.09-1.19, I2 = 0%) were significantly higher.

CONCLUSION

This study identified histidine, methionine, asparagine, hypoxanthine, and glycine as significantly correlated with RA, thus offering the potential for the advancement of biomarker discovery and the elucidation of disease mechanisms in RA.

Comprehensive multi-omics analysis reveals the core role of glycerophospholipid metabolism in rheumatoid arthritis development

OBJECTIVES

Rheumatoid arthritis (RA) is a chronic autoimmune disease with complex causes and recurrent attacks that can easily develop into chronic arthritis and eventually lead to joint deformity. Our study aims to elucidate potential mechanism among control, new-onset RA (NORA) and chronic RA (CRA) with multi-omics analysis.

METHODS

A total of 113 RA patients and 75 controls were included in our study. Plasma and stool samples were obtained for 16S rRNA sequencing, internally transcribed spacer (ITS) sequencing and metabolomics analysis. And PBMCs were obtained for RNA sequencing. We used three models, logistic regression, least absolute shrinkage and selection operator (LASSO), and random forest, respectively, to distinguish NORA from CRA, and finally we validated model performance using an external cohort of 26 subjects.

RESULTS

Our results demonstrated intestinal flora disturbance in RA development, with significantly increased abundance of Escherichia-Shigella and Proteobacteria in NORA. We also found that the diversity was significantly reduced in CRA compared to NORA through fungi analysis. Moreover, we identified 29 differential metabolites between NORA and CRA. Pathway enrichment analysis revealed significant dysregulation of glycerophospholipid metabolism and phenylalanine metabolism pathways in RA patients. Next, we identified 40 differentially expressed genes between NORA and CRA, which acetylcholinesterase (ACHE) was the core gene and significantly enriched in glycerophospholipid metabolism pathway. Correlation analysis showed a strong negatively correlation between glycerophosphocholine and inflammatory characteristics. Additionally, we applied three approaches to develop disease classifier models that were based on plasma metabolites and gut microbiota, which effectively distinguished between new-onset and chronic RA patients in both discovery cohort and external validation cohort.

CONCLUSIONS

These findings revealed that glycerophospholipid metabolism plays a crucial role in the development and progression of RA, providing new ideas for early clinical diagnosis and optimizing treatment strategies.

Exploring the causal correlations between 486 serum metabolites and systemic lupus erythematosus: a bidirectional Mendelian randomization study

Objective: The observational association between circulating metabolites and systemic lupus erythematosus (SLE) has been well documented. However, whether the association is causal remains unclear. In this study, bidirectional Mendelian randomization (MR) was introduced to analyse the causal relationships and possible mechanisms. Methods: We conducted a two-sample bidirectional MR study. A genome-wide association study (GWAS) with 7,824 participants provided data on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS summary, which contained 5,201 single nucleotide polymorphisms (SNPs) cases and 9,066 control cases of Europeans and yielded a total of 7,071,163 SNPs. The inverse variance weighted (IVW) model was recruited as the primary two-sample MR analysis approach, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, leave-one-out analysis, and linkage disequilibrium score (LDSC) regression. Results: In this study, we discovered that 24 metabolites belonging to the lipid, carbohydrate, xenobiotic and amino acid superpathways may increase the risk of SLE occurrence (p < 0.05). In addition, the metabolic disorders of 51 metabolites belonging to the amino acid, energy, xenobiotics, peptide and lipid superpathways were affected by SLE (p < 0.05). Palmitoleate belonging to the lipid superpathway and isobutyrylcarnitine and phenol sulfate belonging to the amino acid superpathway were factors with two-way causation. The metabolic enrichment pathway of bile acid biosynthesis was significant in the forward MR analysis (p = 0.0435). Linolenic acid and linoleic acid metabolism (p = 0.0260), betaine metabolism (p = 0.0314), and glycerolipid metabolism (p = 0.0435) were the significant metabolically enriched pathways in the reverse MR analysis. Conclusion: The levels of some specific metabolites may either contribute to the immune response inducing SLE, or they may be intermediates in the development and progression of SLE. These metabolites can be used as auxiliary diagnostic tools for SLE and for the evaluation of disease progression and therapeutic effects.

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.

Gut microbiota and atopic dermatitis: a two-sample Mendelian randomization study

Background

Accumulating evidence suggests that alterations in gut microbiota composition and diversity are associated with Atopic dermatitis (AD). But until now, the causal association between them has been unclear.

Methods

We employed a two-sample Mendelian Randomization (MR) study to estimate the potential causality of gut microbiota on AD risk. The summary statistics related to the gut microbiota were obtained from a large-scale genome-wide genotype and 16S fecal microbiome dataset from 18,340 individuals (24 cohorts) analyzed by the MiBioGen Consortium, comprising 211 gut microbiota. AD data were also derived from strictly defined AD data collected by FinnGen biobank analysis, which included 218,467 European ancestors (5,321 AD patients and 213,146 controls). The inverse variance weighted method (IVW), weighted median (WME), and MR-Egger were used to determine the changes of AD pathogenic bacterial taxa, followed by sensitivity analysis including horizontal pleiotropy analysis, Cochran's Q test, and the leave-one-out method to assess the reliability of the results. In addition, MR Steiger's test was used to test the suppositional relationship between exposure and outcome.

Results

A total of 2,289 SNPs (p < 1 × 10^-5) were included, including 5 taxa and 17 bacterial characteristics (1 phylum, 3 classes, 1 order, 4 families, and 8 genera), after excluding the IVs with linkage disequilibrium (LD). Combining the analysis of the results of the IVW models, there were 6 biological taxa (2 families, and 4 genera) of the intestinal flora positively associated with the risk of AD and 7 biological taxa (1 phylum, 2 classes, 1 order, 1 family, and 2 genera) of the intestinal flora negatively associated. The IVW analysis results showed that Tenericutes, Mollicutes, Clostridia, Bifidobacteriaceae, Bifidobacteriales, Bifidobacterium, and Christensenellaceae R 7 group were negatively correlated with the risk of AD, while Clostridiaceae 1, Bacteroidaceae, Bacteroides, Anaerotruncus, the unknown genus, and Lachnospiraceae UCG001 showed the opposite trend. And the results of the sensitivity analysis were robust. MR Steiger's test showed a potential causal relationship between the above intestinal flora and AD, but not vice versa.

Conclusion

The present MR analysis genetically suggests a causal relationship between changes in the abundance of the gut microbiota and AD risk, thus not only providing support for gut microecological therapy of AD but also laying the groundwork for further exploration of the mechanisms by which the gut microbiota contributes to the pathogenesis of AD.

Toddalia asiatica extract attenuates adjuvant-induced arthritis by modulating colon Th17/Treg balance and colony homeostasis

ETHNOPHARMACOLOGICAL RELEVANCE

Given the adverse effects of the current principal treatments, there is still a great need for effective cures for rheumatoid arthritis (RA), an immune-mediated disease. Toddalia asiatica (L.) Lam is a traditional medicinal herb that can be used for RA treatment because of its anti-inflammatory and analgesic properties.

AIM OF THE STUDY

To investigate the possible effects of Toddalia asiatica extract (TAE) on intestinal immunity and the intestinal bacterial flora in a rat model of RA.

MATERIALS AND METHODS

The anti-arthritis effect of TAE was evaluated in arthritis rats induced by complete Freund's adjuvant-induced arthritis (AIA). Arthritis index (AI) scores, systemic inflammation scores, histopathologic changes in the colon and ankle were detected by hematoxylin and eosin staining. Western blot analysis was performed to assess the protein expression of IL-17A, RORC, IL-1β, IL-6, FOXP3, IL-10 in the colon. RT-PCR was performed to assess the expression of the colon's mRNA. Finally, changes to the gut microbiome by sequencing 16S rDNA. Microbial function prediction was performed using PICRUSt with the KEGG databases and correlation analysis was carried out by computing Spearman's rank correlations.

RESULTS

demonstrated that TAE administration at a dose of 3 g/kg dramatically decreased AI scores, systemic inflammation scores, and histopathologic lesions of the ankle and colon in AIA rats. TAE was found to significantly reduce the expression levels of Th17-related proteins and mRNAs (IL-17A, RORC, IL-1β and IL-6) in the colon, while increasing the expression levels of Treg-related proteins and mRNA (IL-10 and FOXP3), which helped restore the balance of Th17/Treg immune cells in the colon. Meanwhile, TAE was also found to be capable of remodeling the gut microbiota in AIA rats. Depleting RA-associated genera and thereby increasing α-diversity enriched the gut microbiota's diversity and shifted the community composition dramatically, leading to the increase of Firmicutes_unclassified, Ruminococcaceae_unclassified, Muribaculum, Subdoligranulum, Lachnospira, Marvinbryantia, and the reduction of RA-related bacteria Ligilactobacillus, Streptococcus and Eubacterium-eligens-group. Furthermore, PICRUSt analysis revealed that metabolic pathways were associated with TAE treatment, with metabolic pathways dominating. Among them, metabolic pathways were predominant. Correlation studies showed that a total of 9 microorganisms, including Ligilactobacillus, Eubacterium-eligens-group and Subdoligranulum, were significantly associated with Th17/Treg expression.

CONCLUSIONS

This study demonstrates that TAE is a low-toxicity poly alkaline drug that can rapidly and effectively improve joint symptoms in RA rats and increases beneficial intestinal bacteria and decreases harmful ones, which is associated with modulating Th17/Treg interactions in intestinal T cells and reversing microbial disorders.

Pivotal Role of Intestinal Microbiota and Intraluminal Metabolites for the Maintenance of Gut-Bone Physiology

Intestinal microbiota, and their mutual interactions with host tissues, are pivotal for the maintenance of organ physiology. Indeed, intraluminal signals influence adjacent and even distal tissues. Consequently, disruptions in the composition or functions of microbiota and subsequent altered host-microbiota interactions disturb the homeostasis of multiple organ systems, including the bone. Thus, gut microbiota can influence bone mass and physiology, as well as postnatal skeletal evolution. Alterations in nutrient or electrolyte absorption, metabolism, or immune functions, due to the translocation of microbial antigens or metabolites across intestinal barriers, affect bone tissues, as well. Intestinal microbiota can directly and indirectly alter bone density and bone remodeling. Intestinal dysbiosis and a subsequently disturbed gut-bone axis are characteristic for patients with inflammatory bowel disease (IBD) who suffer from various intestinal symptoms and multiple bone-related complications, such as arthritis or osteoporosis. Immune cells affecting the joints are presumably even primed in the gut. Furthermore, intestinal dysbiosis impairs hormone metabolism and electrolyte balance. On the other hand, less is known about the impact of bone metabolism on gut physiology. In this review, we summarized current knowledge of gut microbiota, metabolites and microbiota-primed immune cells in IBD and bone-related complications.