Found programs: National Natural Science Foundation of China(No.82260894);PhD research project of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine(No.GZEYK-B[2021] No.2);Scientific and Technological Project of Guizhou Province(No.Guizhou Provincial Platform and Talent Program [2020] No.2202);Key Laboratory Project in Universities of Guizhou Province(No.Qianjiaoji [2023] No.017);National and Provincial Science and Technology Innovation Talent Team Cultivation Project of Guizhou University of Traditional Chinese Medicine(No.Guizhou University of Traditional Chinese Innovative talent team cultivation project [2022] No.004);Special Project of the State Key Laboratory of Dampness Syndrome of Chinese Medicine Co-built by the Ministry and Province(No.SZ2021ZZ0202)
Authors：Yi Hanzhi ;Ma Wukai; Wang Minhui; Huang Chunxia; Gu Guangzhao; Zhu Dan; Li Hufan; Liu Can; Tang Fang; Yao Xueming;Sun Liping; Wang Nan; Chen Changming
Keywords：rheumatoid arthritis;osteoarthritis;urarthritis;joint cavity effusion;microorganism;metabolomics
DOI：10.19405/j.cnki.issn1000-1492.2024.12.024
〔Abstract〕 Objective To investigate the changes of microorganisms and metabolites in joint effusion of patients with Rheumatoid arthritis(RA), Osteoarthritis(OA) and Urarthritis(UA). To provide new ideas for the study of the effect of microbiota on the pathogenesis of arthritis. Methods Joint effusion samples were collected from 20 patients with RA, 20 patients with OA, and 20 patients with UA. 16S rRNA gene sequencing and untargeted ultra-high performance Liquid chromatography-mass spectrometry(LC-MS) were used to explore the differences in microorganisms and metabolites among the three groups. Pearson correlation analysis was used to detect the correlation between effusion microbiota and metabolites. Results There were differences in microbial diversity and microbiota composition among the three groups. Combined with VIP>1 from OPLS-DA andP<0.05 from two-tailed Students t-test, 45 differential metabolites(Between RA and OA groups), 38 differential metabolites(Between UA and OA groups) and 16 differential metabolites(Between RA and UA groups), were identified. GO analysis and KEGG pathway analysis showed that the differential metabolic pathways among the three groups were mainly concentrated in citric acid cycle(TCA cycle), nucleotide metabolism, amino acid metabolism and glycolysis pathway. Correlation analysis of joint effusion microbiota and metabolites suggested that bacteria enriched in the three groups of joint effusion, such asPrevotella,Clostridium ruminosus,Prevotellaceae＿UCG-001, were related to many key metabolites such as lysozyme, uric acid, glucose, and L-glutamine. Conclusion This study shows that there are a variety of bacterial flora in joint cavity effusion of RA, OA, and UA patients, and the differential metabolites produced by them are involved in the pathogenesis of the three types of arthritis by affecting a variety of metabolic pathways.