AUTHOR=Zhu Jing , Wang Tingting , Lin Yifei , Xiong Minghao , Chen Jianghua , Jian Congcong , Zhang Jie , Xie Huanhuan , Zeng Fanwei , Huang Qian , Su Jiang , Zhao Yi , Li Shilin , Zeng Fanxin 

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

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.931431

DOI=10.3389/fmicb.2022.931431

ISSN=1664-302X

ABSTRACT=Objective: Rheumatoid 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 the role of them in pathogenesis of RA.
Methods: Metabolomic profiling of plasma from 363 participants including RA (n = 244), systemic lupus erythematosus (n = 50), healthy control (HC, n = 69), were performed using the ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The differential metabolites were selected and to explore important metabolic pathways among groups. Gut microbial diversity analysis were performed by 16S rRNA sequencing and ITS sequencing (RA=195, HC=269), and the specific microbial floras were identified afterwards. The diagnosis models were established based on significant differential metabolites and microbial floras, respectively.
Results: There were 63 differential metabolites discovered between RA and HC groups. The significant metabolic pathways were arginine and proline metabolism, glycine, serine and threonine metabolism, 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, glycerophosphocholine (all p < 0.01). The L-arginine and phosphorylcholine were increased in RA group. The AUC of predictive model was 0.992, based on the combination of the 10 differential metabolites. On 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 3 bacteria genera (Eubacterium_hallii_group, Escherichia-Shigella, Streptococcus) and 2 fungal genera (Candida and Debaryomyces) significantly increased in RA patients. The AUC of ROC was 0.80 based on combine of 6 differential bacterial genera and the AUC was 0.812 based on combine of 7 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". 
Conclusion: The 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.