Dataset Information

The Gut Microbiome and Metabolites Are Altered and Interrelated in Patients With Rheumatoid Arthritis.

ABSTRACT: The relationship among the gut microbiome, global fecal metabolites and rheumatoid arthritis (RA) has not been systematically evaluated. In this study, we performed 16S rDNA sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based nontargeted metabolomic profiling on feces of 26 untreated RA patients and 26 healthy controls. Twenty-six genera and forty-one MS2-identified metabolites were significantly altered in the RA patients. Klebsiella, Escherichia, Eisenbergiella and Flavobacterium were more abundant in the RA patients, while Fusicatenibacter, Megamonas and Enterococcus were more abundant in the healthy controls. Function prediction analysis demonstrated that the biosynthesis pathways of amino acids, such as L-arginine and aromatic amino acids, were depleted in the RA group. In the metabolome results, fecal metabolites including glycerophospholipids (PC(18:3(9Z,12Z,15Z)/16:1(9Z)), lysoPE 19:1, lysoPE 18:0, lysoPC(18:0/0:0)), sphingolipids (Cer(d18:0/16:0), Cer(d18:0/12:0), Cer(d18:0/14:0)), kynurenic acid, xanthurenic acid and 3-hydroxyanthranilic acid were remarkably altered between the RA patients and healthy controls. Dysregulation of pathways, such as tryptophan metabolism, alpha-linolenic acid metabolism and glycerophospholipid metabolism, may contribute to the development of RA. Additionally, we revealed that the gut microbiome and metabolites were interrelated in the RA patients, while Escherichia was the core genus. By depicting the overall landscape of the intestinal microbiome and metabolome in RA patients, our study could provide possible novel research directions regarding RA pathogenesis and targeted therapy.

SUBMITTER: Yu D

PROVIDER: S-EPMC8821809 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Gut Microbiome and Metabolites Are Altered and Interrelated in Patients With Rheumatoid Arthritis.

Yu Die D Du Juping J Pu Xia X Zheng Liyuan L Chen Shuaishuai S Wang Na N Li Jun J Chen Shiyong S Pan Shaobiao S Shen Bo B

Frontiers in cellular and infection microbiology 20220125

The relationship among the gut microbiome, global fecal metabolites and rheumatoid arthritis (RA) has not been systematically evaluated. In this study, we performed 16S rDNA sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based nontargeted metabolomic profiling on feces of 26 untreated RA patients and 26 healthy controls. Twenty-six genera and forty-one MS2-identified metabolites were significantly altered in the RA patients. Klebsiella, Escherichia, Eis ...[more]

PMID: 35145919

Similar Datasets

Project description:BackgroundPatients with rheumatoid arthritis (RA) showed impaired immune tolerance characterized by reduced follicular regulatory T (Tfr) cells, and they also exhibited altered gut microbiotas and their metabolites in RA. However, the association of gut microbiotas and their metabolites with the immune tolerance mediated by Tfr cells in RA remains unclear.MethodsPeripheral blood and stool samples were collected from 32 new-onset RA patients and 17 healthy controls (HCs) in the Second Hospital of Shanxi Medical University between January 2022 and June 2022. The peripheral blood was used to detect the circulating regulatory T (Treg), helper T(Th)17, Tfr, and follicular helper T (Tfh) cells by modified flow cytometry. The stool samples were used to analyze the gut microbiotas and their metabolites via 16S rDNA sequencing and metabolomic profiling. We aimed to characterize the gut microbiotas and their metabolites in RA and identified their association with Tfr cell-mediated immune tolerance.ResultsThe new-onset RA demonstrated reduced Treg and Tfr cells, associated with the disease activity and autoantibodies. There were significant differences in gut microbiotas between the two groups as the results of β diversity analysis (P = 0.039) including 21 differential gut microbiotas from the phylum to genus levels. In which, Ruminococcus 2 was associated with the disease activity and autoantibodies of RA, and it was identified as the potential biomarker of RA [area under curve (AUC) = 0.782, 95% confidence interval (CI) = 0.636-0.929, P = 0.001]. Eleven differential metabolites were identified and participated in four main pathways related to RA. Arachidonic acid might be the potential biomarker of RA (AUC = 0.724, 95% CI = 0.595-0.909, P = 0.038), and it was the core metabolite as the positive association with six gut microbiotas enriched in RA. The reduced Tfr cells were associated with the altered gut microbiotas and their metabolites including the Ruminococcus 2, the arachidonic acid involved in the biosynthesis of unsaturated fatty acid pathway and the 3-methyldioxyindole involved in the tryptophan metabolism pathway.ConclusionThe breakdown of immune tolerance mediated by reduced Tfr cells was associated with the altered gut microbiotas and their metabolites implying the possible mechanism of RA pathogenesis from the perspective of microecology-metabolism-immune.

Project description:ObjectiveRheumatoid arthritis (RA) is a chronic inflammatory joint disease, which is associated with progressive disability, systemic complications, and early death. But its etiology and pathogenesis are not fully understood. We aimed to investigate the alterations in plasma metabolite profiles, gut bacteria, and fungi and their role of them in the pathogenesis of RA.MethodsMetabolomics profiling of plasma from 363 participants including RA (n = 244), systemic lupus erythematosus (SLE, n = 50), and healthy control (HC, n = 69) were performed using the ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The differentially expressed metabolites were selected among groups and used to explore important metabolic pathways. Gut microbial diversity analysis was performed by 16S rRNA sequencing and ITS sequencing (RA = 195, HC = 269), and the specific microbial floras were identified afterward. The diagnosis models were established based on significant differential metabolites and microbial floras, respectively.ResultsThere were 63 differential metabolites discovered between RA and HC groups, mainly significantly enriched in the arginine and proline metabolism, glycine, serine, and threonine metabolism, and glycerophospholipid metabolism between RA and HC groups. The core differential metabolites included L-arginine, creatine, D-proline, ornithine, choline, betaine, L-threonine, LysoPC (18:0), phosphorylcholine, and glycerophosphocholine. The L-arginine and phosphorylcholine were increased in the RA group. The AUC of the predictive model was 0.992, based on the combination of the 10 differential metabolites. Compared with the SLE group, 23 metabolites increased and 61 metabolites decreased in the RA group. However, no significant metabolic pathways were enriched between RA and SLE groups. On the genus level, a total of 117 differential bacteria genera and 531 differential fungal genera were identified between RA and HC groups. The results indicated that three bacteria genera (Eubacterium_hallii_group, Escherichia-Shigella, Streptococcus) and two fungal genera (Candida and Debaryomyces) significantly increased in RA patients. The AUC was 0.80 based on a combination of six differential bacterial genera and the AUC was 0.812 based on a combination of seven differential fungal genera. Functional predictive analysis displayed that differential bacterial and differential fungus both were associated with KEGG pathways involving superpathway of L-serine and glycine biosynthesis I, arginine, ornithine, and proline interconversion.ConclusionThe plasma metabolism profile and gut microbe profile changed markedly in RA. The glycine, serine, and threonine metabolism and arginine and proline metabolism played an important role in RA.

Project description:ObjectiveThe study objective was to compare the microbial composition of patients with dermatomyositis (DM) and healthy controls (HCs) and determine whether microbial alterations are associated with clinical manifestations of DM.MethodsThe 16S ribosomal RNA gene sequencing was performed on fecal samples from patients with DM and HCs. Microbial composition and diversity were compared between subjects with DM and HCs and in association with several DM-specific clinical variables, including myositis-specific autoantibodies (MSAs). Differentially abundant microbial taxa and genes associated with clinical characteristics were identified, and functional analysis was performed using predicted metagenomics. Dietary intake was assessed using a 24-hour dietary recall.ResultsThe fecal microbiome of 36 patients with DM and 26 HCs were analyzed. Patients with DM trended toward lower microbial diversity compared with HCs. The higher physician global damage score was significantly correlated with the lower microbial diversity in patients with DM. Patients with interstitial lung disease (ILD)-associated MSA (antisynthetase antibody (ab), anti-melanoma differentiation-associated protein 5 ab, n = 12) had significant differences in microbial composition and lower microbial diversity compared with HCs. Differential abundance testing demonstrated a unique taxonomic signature in the ILD-MSA subgroup, and predictive metagenomics identified functional alterations in a number of metabolic pathways. A significant increase in the relative abundance of Proteobacteria was positively correlated with multiple pathways involved in lipopolysaccharide synthesis and transport in the ILD-MSA group.ConclusionPatients with DM, particularly with ILD-associated MSAs, have lower microbial diversity and a distinct taxonomic composition compared with HCs. Further studies are needed to validate our findings and elucidate specific pathogenetic mechanisms that link the gut microbiome to clinical and pathological features of DM.

Dataset Information

The Gut Microbiome and Metabolites Are Altered and Interrelated in Patients With Rheumatoid Arthritis.

Publications

The Gut Microbiome and Metabolites Are Altered and Interrelated in Patients With Rheumatoid Arthritis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets