Serum amino acid metabolic profiles of ankylosing spondylitis by targeted metabolomics analysis

Assessing the Genetic Causal Effects Between Blood Metabolites and Spinal Pain: A Bidirectional Two-Sample Mendelian Randomization Study

Background

Previous metabolomics studies have indicated a close association between blood metabolites and pain. However, the causal relationship between blood metabolites and spinal pain (SP) remains unclear. This study employs a bidirectional two-sample Mendelian randomization (MR) analysis to evaluate the causal relationship between 452 blood metabolites and SP.

Methods

We used bidirectional two-sample MR analysis to assess the causal relationship between blood metabolites and SP, including neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). Genome-wide association studies (GWAS) data for 452 metabolites (7,824 participants) were used as exposure variables. Summary data for NP were obtained from the UK Biobank, for TSP from the FinnGen Biobank, and for LBP from both the UK Biobank and the FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. Inverse-variance weighting (IVW) was used to estimate the causal relationships between metabolites and SP, complemented by various sensitivity analyses to account for pleiotropy and heterogeneity, ensuring robust results.

Results

The IVW analysis identified 155 metabolites associated with SP risk and 142 metabolites influenced by SP. No significant heterogeneity or horizontal pleiotropy was observed through other analytical methods.

Conclusion

This study demonstrates potential causal effects between blood metabolites and SP, providing new insights into the pathogenesis of SP. These findings lay a theoretical foundation for preventing and treating SP through targeted interventions on specific blood metabolites, potentially elucidating underlying biological mechanisms.

Serum metabolomics reveals the metabolic profile and potential biomarkers of ankylosing spondylitis

Ankylosing spondylitis (AS) is a chronic systemic inflammatory disease that significantly impairs physical function in young individuals. However, the identification of radiographic changes in AS is frequently delayed, and the diagnostic efficacy of biomarkers like HLA-B27 remains moderately effective, with unsatisfactory sensitivity and specificity. In contrast to existing literature, our current experiment utilized a larger sample size and employed both untargeted and targeted UHPLC-QTOF-MS/MS based metabolomics to identify the metabolite profile and potential biomarkers of AS. The results indicated a notable divergence between the two groups, and a total of 170 different metabolites were identified, which were associated with the 6 primary metabolic pathways exhibiting a correlation with AS. Among these, 26 metabolites exhibited high sensitivity and specificity with area under curve (AUC) values greater than 0.8. Subsequent targeted quantitative analysis discovered 3 metabolites, namely 3-amino-2-piperidone, hypoxanthine and octadecylamine, exhibiting excellent distinguishing ability based on the results of the ROC curve and the Random Forest model, thus qualifying as potential biomarkers for AS. Summarily, our untargeted and targeted metabolomics investigation offers novel and precise insights into potential biomarkers for AS, potentially enhancing diagnostic capabilities and furthering the comprehension of the condition's pathophysiology.

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Exploring the role of gut microbes in spondyloarthritis: Implications for pathogenesis and therapeutic strategies

The gut microbiota plays a pivotal role in regulating host immunity, and dysregulation of this interaction is implicated in autoimmune and inflammatory diseases, including spondyloarthritis (SpA). This review explores microbial dysbiosis and altered metabolic function observed in various forms of SpA, such as ankylosing spondylitis (AS), psoriatic arthritis (PsA), acute anterior uveitis (AAU), and SpA-associated gut inflammation. Studies on animal models and clinical samples highlight the association between gut microbial dysbiosis, metabolic perturbations and immune dysregulation in SpA pathogenesis. These studies have received impetus through next-generation sequencing methods, which have enabled the characterization of gut microbial composition and function, and host gene expression. Microbial/metabolomic studies have revealed potential biomarkers and therapeutic targets, such as short-chain fatty acids, and tryptophan metabolites, offering insights into disease mechanisms and treatment approaches. Further studies on microbial function and its modulation of the immune response have uncovered molecular mechanisms underlying various SpA. Understanding the complex interplay between microbial community structure and function holds promise for improved diagnosis and management of SpA and other autoimmune disorders.

Gut microbiome and metabolome to discover pathogenic bacteria and probiotics in ankylosing spondylitis

Objective

Previous research has partially revealed distinct gut microbiota in ankylosing spondylitis (AS). In this study, we performed non-targeted fecal metabolomics in AS in order to discover the microbiome-metabolome interface in AS. Based on prospective cohort studies, we further explored the impact of the tumor necrosis factor inhibitor (TNFi) on the gut microbiota and metabolites in AS.

Methods

To further understand the gut microbiota and metabolites in AS, along with the influence of TNFi, we initiated a prospective cohort study. Fecal samples were collected from 29 patients with AS before and after TNFi therapy and 31 healthy controls. Metagenomic and metabolomic experiments were performed on the fecal samples; moreover, validation experiments were conducted based on the association between the microbiota and metabolites.

Results

A total of 7,703 species were annotated using the metagenomic sequencing system and by profiling the microbial community taxonomic composition, while 50,046 metabolites were identified using metabolite profiling. Differential microbials and metabolites were discovered between patients with AS and healthy controls. Moreover, TNFi was confirmed to partially restore the gut microbiota and the metabolites. Multi-omics analysis of the microbiota and metabolites was performed to determine the associations between the differential microbes and metabolites, identifying compounds such as oxypurinol and biotin, which were correlated with the inhibition of the pathogenic bacteria Ruminococcus gnavus and the promotion of the probiotic bacteria Bacteroides uniformis. Through experimental studies, the relationship between microbes and metabolites was further confirmed, and the impact of these two types of microbes on the enterocytes and the inflammatory cytokine interleukin-18 (IL-18) was explored.

Conclusion

In summary, multi-omics exploration elucidated the impact of TNFi on the gut microbiota and metabolites and proposed a novel therapeutic perspective: supplementation of compounds to inhibit potential pathogenic bacteria and to promote potential probiotics, therefore controlling inflammation in AS.

A systematic review and meta-analysis of the kynurenine pathway of tryptophan metabolism in rheumatic diseases

There is an increasing interest in the pathophysiological role of the kynurenine pathway of tryptophan metabolism in the regulation of immune function and inflammation. We sought to address the link between this pathway and the presence rheumatic diseases (RD) by conducting a systematic review and meta-analysis of studies reporting the plasma or serum concentrations of tryptophan, kynurenine, and other relevant metabolites in RD patients and healthy controls. We searched electronic databases for relevant articles published between inception and the 30th of June 2023. Risk of bias and certainty of evidence were assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Grades of Recommendation, Assessment, Development and Evaluation Working Group system. In 24 studies selected for analysis, compared to controls, RD patients had significantly lower tryptophan (standard mean difference, SMD= -0.71, 95% CI -1.03 to -0.39, p<0.001; I2 = 93.6%, p<0.001; low certainty of evidence), and higher kynurenine (SMD=0.69, 95% CI 0.35 to 1.02, p<0.001; I2 = 93.2%, p<0.001; low certainty), kynurenine to tryptophan ratios (SMD=0.88, 95% CI 0.55 to 1.21, p<0.001; I2 = 92.9%, p<0.001; moderate certainty), 3-hydroxykynurenine (SMD=0.74, 95% CI 0.30 to 1.18, p=0.001; I2 = 87.7%, p<0.001; extremely low certainty), and quinolinic acid concentrations (SMD=0.71, 95% CI 0.31 to 1.11, p<0.001; I2 = 88.1%, p<0.001; extremely low certainty). By contrast, there were non-significant between-group differences in kynurenic acid, 3-hydroxyanthranilic acid, kynurenic acid to kynurenine ratio, or quinolinic acid to kynurenine acid ratio. In meta-regression, the SMD of tryptophan, kynurenine, and kynurenine to tryptophan ratio were not associated with age, publication year, sample size, RD duration, C-reactive protein, or use of anti-rheumatic drugs and corticosteroids. In subgroup analysis, the SMD of tryptophan, kynurenine, and kynurenine to tryptophan ratio was significant across different types of RD, barring rheumatoid arthritis. Therefore, we have observed significant alterations in tryptophan, kynurenine, 3-hydroxykynurenine, and quinolinic acid concentrations in RD patients. Further research is warranted to determine whether these biomarkers can be useful for diagnosis and management in this patient group. (PROSPERO registration number: CRD CRD42023443718).

Systematic review registration

https://www.crd.york.ac.uk/prospero, identifier CRD CRD42023443718.

Role of HLA class I and II alleles in susceptibility to ankylosing spondylitis in Chinese Han

OBJECTIVE

The objective of the study was to clarify the associations of HLA class I and II alleles with ankylosing spondylitis (AS) among Chinese Han.

METHODS

We performed HLA genotyping and Sanger sequencing for 68 HLA-B*27(-), 62 HLA-B*27(+) AS patients, and 70 controls. Case-control analyses and separate analyses of HLA-B*27(-) patients were performed. One-way ANOVA and Kruskal-Wallis multiple comparisons test were used to analyze the effects of HLA-A\B\C\DRB1\DQB1 alleles on clinical characteristics of HLA-B*27(-) and HLA-B*27(+) patients.

RESULTS

In the HLA-B*27(+) group, positive associations were seen with A*11:02, B*27:04, B*27:05, C*02:02, C*12:02, and DRB1*04:01 and negative associations were seen with A*33:03, B*07:02, B*57:01, and C*07:02. The age at onset was greater in HLA-B*27(-) patients than in HLA-B*27(+) patients (30.03 ± 15.15 vs. 23.08 ± 7.79 years). In the HLA-B*27(-) group, those with A*01:01, B*13:01, B*13:02, C*01:02, C*04:01, DQB1*02:01, DQB1*06:01, and DRB1*03:01 had an earlier onset than those without these alleles, while patients carrying B*40:02, C*07:02, C*12:02, C*15:02, DQB1*05:02, and DQB1*05:03 had a delayed onset. In the HLA-B*27(-) group, A*32:01(+), C*08:01(+), and DRB1*04:05(-) women were likely to develop AS. In the HLA-B*27(+) group, DQB1*03:02(+) women may be more likely to develop AS. DRB1*12:02 and HLA-B*27 interacted with the distribution of AS-affected sites. In the HLA-B*27(+) group, DRB1*12:02(+) patients were likely to have peripheral joint involvement.

CONCLUSION

HLA class I and II alleles other than HLA-B*27 contribute to AS predisposition and characteristics among Chinese Han patients.

Diagnostic serum biomarkers associated with ankylosing spondylitis

Ankylosing spondylitis (AS) is an autoimmune rheumatic disease that mostly affects the axial skeleton. This study aimed to investigate reliable diagnostic serum biomarkers for AS. Serum samples were collected from 20 AS patients and 20 healthy controls (HCs) and analyzed using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The differential metabolites between the AS patients and HCs were profiled using univariate and multivariate statistical analyses. Pathway analysis and a heat map were also conducted. Random forest (RF) analysis and the least absolute shrinkage and selection operator (LASSO) were used to establish predictive and diagnostic models. After controlling the variable importance in the projection (VIP) value > 1 and false discovery rate (FDR) < 0.05, a total of 61 differential metabolites were identified from 995 metabolites, which exhibited significant differences in the pathway analysis and heat map between the AS patients and HCs. RF as a predictive model also identified differential metabolites with 95% predictive accuracy and a high area under the curve (AUC) of 1. A diagnostic model comprising nine metabolites (cysteinylglycine disulfide, choline, N6, N6, N6-trimethyllysine, histidine, sphingosine, fibrinopeptide A, glycerol 3-phosphate, 1-linoleoyl-GPA (18:2), and fibrinopeptide A (3-16)) was generated using LASSO regression, capable of distinguishing HCs from AS with a high AUC of 1. Our results indicated that the UPLC-MS/MS analysis method is a powerful tool for identifying AS metabolite profiles. We developed a nine-metabolites-based model serving as a diagnostic tool to separate AS patients from HCs, and the identified diagnostic biomarkers appeared to have a diagnostic value for AS.

Immunometabolomics provides a new perspective for studying systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic multi-organ autoimmune disease characterized by clinical heterogeneity, unpredictable progression, and flare ups. Due to the heterogeneous nature of lupus, it has been challenging to identify sensitive and specific biomarkers for its diagnosis and monitoring. Despite the fact that the mechanism of SLE remains unknown, impressive progress has been made over the last decade towards understanding how different immune cells contribute to its pathogenesis. Research suggests that cellular metabolic programs could affect the immune response by regulating the activation, proliferation, and differentiation of innate and adaptive immune cells. Many studies have shown that the dysregulation of the immune system is associated with changes to metabolite profiles. The study of metabolite profiling may provide a means for mechanism exploration and novel biomarker discovery for disease diagnostic, classification, and monitoring. Here we review the latest advancements in understanding the role of immunometabolism in SLE, as well as the systemic metabolite profiling of this disease along with possible clinical application.

Temporal metabolic profiling of erythrocytes in mice infected with Babesia microti

BACKGROUND

Babesiosis is an emerging zoonosis worldwide that is caused by tick-borne apicomplexans, Babesia spp., which threatens the health of domesticated and wild mammals and even humans. Although it has done serious harm to animal husbandry and public health, the study of Babesia is still progressing slowly. Until now, no effective anti-Babesia vaccines have been available, and administration of combined drugs tends to produce side effects. Therefore, non-targeted metabolomics was employed in the present study to examine the temporal dynamic changes in the metabolic profile of the infected erythrocytes. The goal was to obtain new insight into pathogenesis of Babesia and to explore vaccine candidates or novel drug targets.

METHODS

C57BL/6 mice were infected with B. microti and erythrocytes at different time points (0, 3, 6 , 9, 12, and 22-days post-infection) were subjected to parasitemia surveillance and then metabolomics analysis using liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses were performed to clearly separate and identify dysregulated metabolites in Babesia-infected mice. The analyses included principal components analysis (PCA) and orthogonal partial least squares-discrimination analysis (OPLS-DA). The time-series trends of the impacted molecules were analyzed using the R package Mfuzz and the fuzzy clustering principle. The temporal profiling of amino acids, lipids, and nucleotides in blood cells infected with B. microti were also investigated.

RESULTS

B. microti infection resulted in a fast increase of parasitemia and serious alteration of the mouse metabolites. Through LC-MS metabolomics analysis, 10,289 substance peaks were detected and annotated to 3,705 components during the analysis period. There were 1,166 dysregulated metabolites, which were classified into 8 clusters according to the temporal trends. Consistent with the trend of parasitemia, the numbers of differential metabolites reached a peak of 525 at 6-days post-infection (dpi). Moreover, the central carbon metabolism in cancer demonstrated the most serious change during the infection process except for that observed at 6 dpi. Sabotage occurred in components involved in the TCA cycle, amino acids, lipids, and nucleotide metabolism.

CONCLUSION

Our findings revealed a great alteration in the metabolites of Babesia-infected mice and shed new light on the pathogenesis of B. microti at the metabolic level. The results might lead to novel information about the mechanisms of pathopoiesis, babesisosis, and anti-parasite drug/vaccine development in the future.

Role of the microbiome and its metabolites in ankylosing spondylitis

Ankylosing spondylitis (AS), a chronic condition that commonly influences the spine and sacroiliac joints, usually progresses to stiffness and progressive functional limitation. Its fundamental etiology and pathogenesis are likely multifactorial and remain elusive. As environmental factors, gut microbiota performs critical functions in the pathogenesis of AS through various mechanisms, including interacting with genes, enhancing intestinal permeability, activating the gut mucosa immune system, and affecting the intestinal microbiota metabolites. This review provides an overview of recent advances in investigating gut microbiota in AS pathogenesis and discusses potential methods for future therapeutic intervention.

Aberrant lncRNA–mRNA expression profile and function networks during the adipogenesis of mesenchymal stem cells from patients with ankylosing spondylitis

Objective: We have already demonstrated that mesenchymal stem cells from patients with ankylosing spondylitis (ASMSCs) exhibited greater adipogenic differentiation potential than those from healthy donors (HDMSCs). Here, we further investigated the expression profile of long noncoding RNA (lncRNA) and mRNA, aiming to explore the underlying mechanism of abnormal adipogenic differentiation in ASMSCs.

Methods: HDMSCs and ASMSCs were separately isolated and induced with adipogenic differentiation medium for 10 days. Thereafter, lncRNAs and mRNAs that were differentially expressed (DE) between HDMSCs and ASMSCs were identified via high-throughput sequencing and confirmed by quantitative real-time PCR (qRT–PCR) assays. Then, the DE genes were annotated and enriched by GO analysis. In addition, protein interaction network was constructed to evaluate the interactions between DE mRNAs and to find hub nodes and study cliques. Besides, co-expression network analysis was carried out to assess the co-expressions between DE mRNA and DE lncRNAs, and competing endogenous RNA (ceRNA) network analysis were conducted to predict the relationships among lncRNAs, mRNAs and miRNAs. The signaling pathways based on the DE genes and the predicted DE genes were enriched by KEGG analysis.

Results: A total of 263 DE lncRNAs and 1376 DE mRNAs were found during adipogenesis in ASMSCs. qRT–PCR indicated that the expression of the top 20 mRNAs and the top 10 lncRNAs was consistent with the high-throughput sequencing data. Several lncRNAs (NR_125386.1, NR_046473.1 and NR_038937.1) and their target genes (SPN and OR1AIP2), together with the significantly co-expressed pairs of DE lncRNAs and DE mRNAs (SLC38A5-ENST00000429588.1, TMEM61-ENST00000400755.3 and C5orf46-ENST00000512300.1), were closely related to the enhanced adipogenesis of ASMSCs by modulating the PPAR signaling pathway.

Conclusion: Our study analyzed the expression profiles of DE lncRNAs and DE mRNAs during adipogenesis in ASMSCs and HDMSCs. Several DE lncRNAs, DE mRNAs and signaling pathways that probably participate in the aberrant adipogenesis of ASMSCs were selected for future study. These results will likely provide potential targets for our intervention on fat metaplasia and subsequent new bone formation in patients with AS in the future.

Axial spondyloarthritis patients have altered mucosal IgA response to oral and fecal microbiota

Axial spondyloarthritis (axSpA) is an inflammatory arthritis involving the spine and the sacroiliac joint with extra-articular manifestations in the eye, gut, and skin. The intestinal microbiota has been implicated as a central environmental component in the pathogenesis of various types of spondyloarthritis including axSpA. Additionally, alterations in the oral microbiota have been shown in various rheumatological conditions, such as rheumatoid arthritis (RA). Therefore, the aim of this study was to investigate whether axSpA patients have an altered immunoglobulin A (IgA) response in the gut and oral microbial communities. We performed 16S rRNA gene (16S) sequencing on IgA positive (IgA⁺) and IgA negative (IgA^-) fractions (IgA-SEQ) from feces (n=17 axSpA; n=14 healthy) and saliva (n=14 axSpA; n=12 healthy), as well as on IgA-unsorted fecal and salivary samples. PICRUSt2 was used to predict microbial metabolic potential in axSpA patients and healthy controls (HCs). IgA-SEQ analyses revealed enrichment of several microbes in the fecal (Akkermansia, Ruminococcaceae, Lachnospira) and salivary (Prevotellaceae, Actinobacillus) microbiome in axSpA patients as compared with HCs. Fecal microbiome from axSpA patients showed a tendency towards increased alpha diversity in IgA⁺ fraction and decreased diversity in IgA^- fraction in comparison with HCs, while the salivary microbiome exhibits a significant decrease in alpha diversity in both IgA⁺ and IgA^- fractions. Increased IgA coating of Clostridiales Family XIII in feces correlated with disease severity. Inferred metagenomic analysis suggests perturbation of metabolites and metabolic pathways for inflammation (oxidative stress, amino acid degradation) and metabolism (propanoate and butanoate) in axSpA patients. Analyses of fecal and salivary microbes from axSpA patients reveal distinct populations of immunoreactive microbes compared to HCs using the IgA-SEQ approach. These bacteria were not identified by comparing their relative abundance alone. Predictive metagenomic analysis revealed perturbation of metabolites/metabolic pathways in axSpA patients. Future studies on these immunoreactive microbes may lead to better understanding of the functional role of IgA in maintaining microbial structure and human health.

Metabolomic analysis in spondyloarthritis: A systematic review

Spondyloarthritis (SpA) is a group of rheumatic diseases that cause joint inflammation. Accumulating studies have focused on the metabolomic profiling of SpA in recent years. We conducted a systematic review to provide a collective summary of previous findings on metabolomic profiling associated with SpA. We systematically searched PubMed, Medline, Embase and Web of Science for studies on comparisons of the metabolomic analysis of SpA patients and non-SpA controls. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included articles. From 482 records identified, 31 studies were included in the analysis. A number of metabolites were differentially distributed between SpA and non-SpA cases. SpA patients showed higher levels of glucose, succinic acid, malic acid and lactate in carbohydrate metabolism, higher glycerol levels and lower fatty acid (especially unsaturated fatty acid) levels in lipid metabolism, and lower levels of tryptophan and glutamine in amino acid metabolism than healthy controls. Both conventional and biological therapy of SpA can insufficiently reverse the aberrant metabolism state toward that of the controls. However, the differences in the results of metabolic profiling between patients with SpA and other inflammatory diseases as well as among patients with several subtypes of SpA are inconsistent across studies. Studies on metabolomics have provided insights into etiological factors and biomarkers for SpA. Supplementation with the metabolites that exhibit decreased levels, such as short-chain fatty acids (SCFAs), has good treatment prospects for modulating immunity. Further studies are needed to elucidate the role of disordered metabolic molecules in the pathogenesis of SpA.

Metabolomics and molecular docking-directed antiarthritic study of the ethyl acetate extract from Celastrus orbiculatus Thunb

ETHNOPHARMACOLOGICAL RELEVANCE

Celastrus orbiculatus Thunb., an important folk medicine, has long been used for the treatment of rheumatoid arthritis and its ethyl acetate extract (COE) has been reported to possess anticancer, antiinflammation and antiarthritic effects. However, the therapeutic effect and mechanism of COE treatment in rheumatoid arthritis has been rarely studied especially from the perspective of metabolomics.

AIM OF STUDY

To reveal the therapeutic effects of COE on adjuvant-induced arthritis (AIA) rats through histopathological analysis, non-targeted metabolomics, and molecular docking study.

MATERIALS AND METHODS

Forty-three Wistar rats were randomly divided into normal group, AIA model group, methotrexate group, and COE groups (80 mg/kg, 160 mg/kg and 320 mg/kg of ethyl acetate extract). Paw swelling and arthritis score were monitored through the experiment. Serum levels of tumor necrosis factor α (TNF-α) and nitric oxide were determined and histopathological evaluation was performed. Furthermore, Ultra-high performance liquid chromatography-linear trap quadrupole-Orbitrap-based metabolomics was employed to characterize metabolic changes of AIA rats after COE treatment and molecular docking was performed to predict the potential phytochemicals of COE against TNF-α.

RESULTS

COE at three dosages could significantly relieve paw swelling and reduce arthritis scores of AIA rat. Histopathological analysis revealed remarkable decrease in synovial inflammation and bone erosion after COE treatment, especially at middle and high dosage. Additionally, COE down-regulated serum levels of TNF-α and nitric oxide. Serum metabolomics showed that 22 potential biomarkers for the COE treatment of AIA rats were identified, which were closely related to fatty acid metabolism, glycerophospholipid catabolism, and tryptophan metabolism. The molecular docking models predicted that olean-type triterpenes in COE may contribute most to therapeutic effects of rheumatoid arthritis through targeting TNF-α.

CONCLUSIONS

COE could significantly relieve the arthritic symptoms in AIA rats and the ultra-high performance liquid chromatography-mass spectrometry based metabolomics proved to be an efficient method to characterize subtle metabolic changes of AIA rats after COE treatment.

Metabolomic profiling in ankylosing spondylitis using time-of-flight mass spectrometry

BACKGROUND & AIMS

Ankylosing spondylitis (AS) is an inflammatory disease associated with destructive changes in the skeleton and joints. The exact molecular mechanism of the disease has not been fully elucidated. This study aimed to determine metabolic differences between active AS patients and healthy controls to understand the molecular mechanism of AS.

PATIENTS AND METHODS

The study included 38 subjects, comprising 18 patients with active AS and 20 healthy controls. Metabolic profiling of the plasma was performed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS). Data acquisition, classification, and identification were achieved with the METLIN (https://metlin.scripps.edu/) database and XCMS (https://xcmsonline.scripps.edu).

RESULTS

Significant alterations were identified in the unsaturated fatty acids (FA), linoleic acid, alpha-linolenic acid, FA degradation, and FA biosynthesis pathways. Down -regulations were observed in phosphatidylcholine (PC) (16:0/0:0), beta-d-Fructose, stearic acid, trimipramine N-Oxide and muconic acid, and up-regulation were detected in PC (18:2/0:0), 3-Methylindole, palmitic acid (PA), alpha-Tocotrienol, and beta-d-glucopyranoside in active AS patients compared to the healthy control subjects.

CONCLUSION

Pathway analysis revealed that dysregulation in FA metabolism is associated with AS, and therefore, modulation of diet according to PA and PC may be potential therapeutic targets.

Serine, N-acetylaspartate differentiate adolescents with juvenile idiopathic arthritis compared with healthy controls: a metabolomics cross-sectional study

BACKGROUND

In comparison with the general population, adolescents with juvenile idiopathic arthritis (JIA) are at higher risk for morbidity and mortality. However, limited evidence is available about this condition's underlying metabolic profile in adolescents with JIA relative to healthy controls. In this untargeted, cross-sectional metabolomics study, we explore the plasma metabolites in this population.

METHODS

A sample of 20 adolescents with JIA and 20 controls aged 13-17 years were recruited to complete surveys, provide medical histories and biospecimens, and undergo assessments. Fasting morning plasma samples were processed with liquid chromatography-mass spectrometry. Data were centered, scaled, and analyzed using generalized linear models accounting for age, sex, and medications (p-values adjusted for multiple comparisons using the Holm method). Spearman's correlations were used to evaluate relationships among metabolites, time since diagnosis, and disease severity.

RESULTS

Of 72 metabolites identified in the samples, 55 were common to both groups. After adjustments, 6 metabolites remained significantly different between groups. Alpha-glucose, alpha-ketoglutarate, serine, and N-acetylaspartate were significantly lower in the JIA group than in controls; glycine and cystine were higher. Seven additional metabolites were detected only in the JIA group; 10 additional metabolites were detected only in the control group. Metabolites were unrelated to disease severity or time since diagnosis.

CONCLUSIONS

The metabolic signature of adolescents with JIA relative to controls reflects a disruption in oxidative stress; neurological health; and amino acid, caffeine, and energy metabolism pathways. Serine and N-acetylaspartate were promising potential biomarkers, and their metabolic pathways are linked to both JIA and cardiovascular disease risk. The pathways may be a source of new diagnostic, treatment, or prevention options. This study's findings contribute new knowledge for systems biology and precision health approaches to JIA research. Further research is warranted to confirm these findings in a larger sample.

Metabolomics: An Emerging Approach to Understand Pathogenesis and to Assess Diagnosis and Response to Treatment in Spondyloarthritis

Spondyloarthritis (SpA) is a group of rheumatic diseases whose pathogenesis relies on a complex interplay between genetic and environmental factors. Over the last several years, the importance of the alteration of the gut microbiota, known as dysbiosis, and the interaction of bacterial products with host immunity have been highlighted as intriguing key players in SpA development. The recent advent of the so called “-omics” sciences, that include metabolomics, opened the way to a new approach to SpA through a deeper characterisation of the pathogenetic mechanisms behind the disease. In addition, metabolomics can reveal potential new biomarkers to diagnose and monitor SpA patients. The aim of this review is to highlight the most recent advances concerning the application of metabolomics to SpA, in particular focusing attention on Ankylosing Spondylitis and Psoriatic Arthritis.

Arginine-induced metabolomic perturbation in Streptococcus mutans

Background

Streptococcus mutans is a major pathogen responsible for dental caries. Arginine is a promising potential caries preventive agent which can inhibit the growth of S. mutans. However, the mechanism whereby arginine inhibits S. mutans growth remains unclear.

Aim

To assess the impact of arginine-induced metabolomic perturbations on S. mutans under biofilm conditions.

Methods

We identified 5,933 and 7,413 ions in positive (ESI+) and negative (ESI-) electrospray ion modes, respectively, with a total of 11.05% and 11.58% differential ions subsequently detected in two respective modes. Further analyses of these metabolites led to identification of 8 and 22 metabolic pathways that were affected by arginine treatment in ESI+ and ESI- modes.,

Results

Once or twice daily treatments of S. mutans biofilms with arginine resulted in reductions in biofilm biomass. Significant reductions in EPS production were observed following twice daily arginine treatments. Identified metabolites that were significantly differentially abundant following arginine treatment were associated with glycolysis metabolism, amino sugar and nucleotide sugar metabolism, and peptidoglycan synthesis.

Conclusions

Arginine can reduce S. mutans biofilm growth and acid production by inhibiting glycolysis, amino sugar and nucleotide sugar metabolism, and peptidoglycan synthesis.

Targeted metabolomics analysis of serum amino acid profiles in patients with Moyamoya disease

Amino acids are one of the main metabolites in the body, and provide energy for the body and brain. The purpose of this study is to provide a profile of amino acid changes in the serum of patients with Moyamoya disease (MMD) and identify potential disease biomarkers. In this paper, we quantitatively determined the serum amino acid metabolic profiles of 43 MMD patients and 42 healthy controls (HCs). T test, multivariate statistical analysis, and receiver operating characteristic (ROC) curve analysis were used to identify candidate markers. Thirty-nine amino acids were quantified, and 12 amino acid levels differed significantly between the MMD patients and HCs. Moreover, based on ROC curve analysis, four amino acid (L-methionine, L-glutamic acid, β-alanine and o-phosphoserine) biomarkers showed high sensitivity and specificity (AUC > 0.90), and showed the best sensitivity and specificity in MetaboAnalyst 5.0 using binary logistic regression analysis. We have provided serum amino acid metabolic profiles of MMD patients, and identified four potential biomarkers which may both provide clinicians with an objective diagnostic method for early detection of MMD and further our understanding of MMD pathogenesis.

Intestinal Microbial Metabolites in Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a chronic inflammatory disease characterized by inflammation of axial joints and the pelvis. It is known that intestinal dysbiosis may exert direct pathogenic effects on gut homeostasis and may act as a triggering factor for the host innate immune system to activate and cause inflammation in extraintestinal sites in the so-called "gut-joint axis", contributing to AS pathogenesis. However, although the intestinal microbiota's influence on the clinical manifestation of AS is widely accepted, the mechanisms mediating the cross-talk between the intestinal lumen and the immune system are still not completely defined. Recent evidence suggests that the metabolism of microbial species may be a source of metabolites and small molecules participating in the complex network existing between bacteria and host cells. These findings may give inputs for further research of novel pharmacological targets and pave the way to applying dietary interventions to prevent the onset and ameliorate the clinical presentation of the disease. In this review, we discuss the role of some of the biological mediators of microbial origin, with a particular focus on short-chain fatty acids, tryptophan and vitamin B derivatives, and their role in barrier integrity and type 3 immunity in the context of AS.

Biomarker identification and pathway analysis of rheumatoid arthritis based on metabolomics in combination with ingenuity pathway analysis

Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease worldwide, but understanding its pathogenesis is still limited. In this study, plasma untargeted metabolomics of a discovery cohort and targeted analysis of a verification cohort were performed by gas chromatograph mass spectrometry (GC/MS). Univariate and multivariate statistical analysis were utilized to reveal differential metabolites, followed by the construction of biomarker panel through random forest (RF) algorithm. The pathways involved in RA were enriched by differential metabolites using Ingenuity Pathway Analysis (IPA) suite. Untargeted metabolomics revealed eighteen significantly altered metabolites in RA. Among these metabolites, a three-metabolite marker panel consisting of L-cysteine, citric acid and L-glutamine was constructed, using random forest algorithm that could predict RA with high accuracy, sensitivity and specificity based on a multivariate exploratory receiver operator characteristic (ROC) curve analysis. The panel was further validated by support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA) algorithms, and also verified with targeted metabolomics using a verification cohort. Additionally, the dysregulated taurine biosynthesis pathway in RA was revealed by an integrated analysis of metabolomics and transcriptomics. Our findings in this study not only provided a mechanism underlying RA pathogenesis, but also offered alternative therapeutic targets for RA.

MG@PD@TiO2 nanocomposite based magnetic solid phase extraction coupled with LC-MS/MS for determination of lysophosphatidylcholines biomarkers of plasma in psoriasis patients

Lysophosphatidylcholine (LPC) was commonly known as a class of significant differential metabolites of high relevance with many diseases including psoriasis, of which the accurate determination is of great importance to diagnosis or prediction to many diseases. However, it is challenging and complicated because of the enormous biological sample complexity and impurities interference. In this study, we synthesized a magnetic nanocomposite MG@PD@TiO₂ and took advantage of the interactions of Lewis acid-base between the phosphate groups in LPCs and Ti ions on MG@PD@TiO₂ nanomaterials for selective separation and enrichment of LPCs from complex biological matrix. The solid-phase extraction sample pretreatment process by means of MG@PD@TiO₂ nanomaterials coupled with LC-MS/MS method was then applied to actual determination of six typical LPCs (LPC 10:0, 14:0, 16:0, 18:0, 18:1, 22:0) in human plasma. The extraction conditions were scientifically optimized by single-factor test (adsorbent amount, adsorption and desorption time, elution solvent type, eluant volume). Under the optimal conditions, the detection limits (LOD, S/N = 3) and quantification limits (LOQ, S/N = 10) were 1 and 5 ng/mL for LPC 10:0 and LPC 14:0, 0.02 and 0.1 ng/mL for LPC 16:0 and LPC 18:1, 0.05 and 0.2 ng/mL LPC 18:0 and LPC 22:0, respectively. The intra- and inter-day precisions were 3.82-12.60 % (n = 6) and 3.29-13.50 % (n = 6) respectively, the recoveries were in the range of 91.92-113.69 % and the stability of the analytes in the matrix performed well with RSDs≤15.51 %. Finally, the developed method was successfully applied to the accurate determination of six LPCs biomarkers of plasma in patients with psoriasis (n = 10) and control groups (n = 10).

Multi 'Omics Analysis of Intestinal Tissue in Ankylosing Spondylitis Identifies Alterations in the Tryptophan Metabolism Pathway

Intestinal microbial dysbiosis, intestinal inflammation, and Th17 immunity are all linked to the pathophysiology of spondyloarthritis (SpA); however, the mechanisms linking them remain unknown. One potential hypothesis suggests that the dysbiotic gut microbiome as a whole produces metabolites that influence human immune cells. To identify potential disease-relevant, microbiome-produced metabolites, we performed metabolomics screening and shotgun metagenomics on paired colon biopsies and fecal samples, respectively, from subjects with axial SpA (axSpA, N=21), Crohn's disease (CD, N=27), and Crohn's-axSpA overlap (CD-axSpA, N=12), as well as controls (HC, N=24). Using LC-MS based metabolomics of 4 non-inflamed pinch biopsies of the distal colon from subjects, we identified significant alterations in tryptophan pathway metabolites, including an expansion of indole-3-acetate (IAA) in axSpA and CD-axSpA compared to HC and CD and indole-3-acetaldehyde (I3Ald) in axSpA and CD-axSpA but not CD compared to HC, suggesting possible specificity to the development of axSpA. We then performed shotgun metagenomics of fecal samples to characterize gut microbial dysbiosis across these disease states. In spite of no significant differences in alpha-diversity among the 4 groups, our results confirmed differences in gene abundances of numerous enzymes involved in tryptophan metabolism. Specifically, gene abundance of indolepyruvate decarboxylase, which generates IAA and I3Ald, was significantly elevated in individuals with axSpA while gene abundances in HC demonstrated a propensity towards tryptophan synthesis. Such genetic changes were not observed in CD, again suggesting disease specificity for axSpA. Given the emerging role of tryptophan and its metabolites in immune function, altogether these data indicate that tryptophan metabolism into I3Ald and then IAA is one mechanism by which the gut microbiome potentially influences the development of axSpA.

Serum Metabolomics Signatures Associated With Ankylosing Spondylitis and TNF Inhibitor Therapy

Ankylosing spondylitis (AS) is a type of spondyloarthropathies, the diagnosis of which is often delayed. The lack of early diagnosis tools often delays the institution of appropriate therapy. This study aimed to investigate the systemic metabolic shifts associated with AS and TNF inhibitors treatment. Additionally, we aimed to define reliable serum biomarkers for the diagnosis. We employed an untargeted technique, ultra-performance liquid chromatography-mass spectroscopy (LC-MS), to analyze the serum metabolome of 32 AS individuals before and after 24-week TNF inhibitors treatment, as well as 40 health controls (HCs). Multivariate and univariate statistical analyses were used to profile the differential metabolites associated with AS and TNF inhibitors. A diagnostic panel was established with the least absolute shrinkage and selection operator (LASSO). The pathway analysis was also conducted. A total of 55 significantly differential metabolites were detected. We generated a diagnostic panel comprising five metabolites (L-glutamate, arachidonic acid, L-phenylalanine, PC (18:1(9Z)/18:1(9Z)), 1-palmitoylglycerol), capable of distinguishing HCs from AS with a high AUC of 0.998, (95%CI: 0.992-1.000). TNF inhibitors treatment could restore the equilibrium of 21 metabolites. The most involved pathways in AS were amino acid biosynthesis, glycolysis, glutaminolysis, fatty acids biosynthesis and choline metabolism. This study characterized the serum metabolomics signatures of AS and TNF inhibitor therapy. We developed a five-metabolites-based panel serving as a diagnostic tool to separate patients from HCs. This serum metabolomics study yielded new knowledge about the AS pathogenesis and the systemic effects of TNF inhibitors.

B cell-derived GABA elicits IL-10+ macrophages to limit anti-tumour immunity

Small, soluble metabolites not only are essential intermediates in intracellular biochemical processes, but can also influence neighbouring cells when released into the extracellular milieu^1-3. Here we identify the metabolite and neurotransmitter GABA as a candidate signalling molecule synthesized and secreted by activated B cells and plasma cells. We show that B cell-derived GABA promotes monocyte differentiation into anti-inflammatory macrophages that secrete interleukin-10 and inhibit CD8⁺ T cell killer function. In mice, B cell deficiency or B cell-specific inactivation of the GABA-generating enzyme GAD67 enhances anti-tumour responses. Our study reveals that, in addition to cytokines and membrane proteins, small metabolites derived from B-lineage cells have immunoregulatory functions, which may be pharmaceutical targets allowing fine-tuning of immune responses.