Background Long non-coding RNA heart and neural crest derivatives expressed 2-antisense RNA 1 (HAND2-AS1) was found to be elevated in rheumatoid arthritis (RA) fibroblast-like synoviocytes (RA-FLSs). However, whether HAND2-AS1 functions as an exosomal lncRNA related to mesenchymal stem cells (MSCs) in RA progression is unknown. Methods The expression of HAND2-AS1, microRNA (miR)-143-3p, and tumor necrosis factor alpha-inducible protein 3 (TNFAIP3) was detected using quantitative real-time polymerase chain reaction and Western blot. Cell proliferation, apoptosis, migration, and invasion were detected using cell counting kit-8, flow cytometry, and wound healing and transwell assays. The levels of tumor necrosis factor-α (TNF-α) and interleukins (IL)-6 were analyzed using enzyme-linked immunosorbent assay. The level of phosphorylated-p65 was examined by Western blot. The binding interaction between miR-143-3p and HAND2-AS1 or TNFAIP3 was confirmed by the dual-luciferase reporter and RIP assays. Exosomes were isolated by ultracentrifugation and qualified by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blot. Results HAND2-AS1 was lowly expressed in RA synovial tissues, and HAND2-AS1 re-expression suppressed the proliferation, motility, and inflammation and triggered the apoptosis in RA-FLSs via the inactivation of NF-κB pathway. Mechanistically, HAND2-AS1 directly sponged miR-143-3p and positively regulated TNFAIP3 expression, the target of miR-143-3p. Moreover, the effects of HAND2-AS1 on RA-FLSs were partially attenuated by miR-143-3p upregulation or TNFAIP3 knockdown. HAND2-AS1 could be packaged into hMSC-derived exosomes and absorbed by RA-FLSs, and human MSC-derived exosomal HAND2-AS1 also repressed above malignant biological behavior of RA-FLSs. Conclusion MSC-derived exosomes participated in the intercellular transfer of HAND2-AS1 and suppressed the activation of RA-FLSs via miR-143-3p/TNFAIP3/NF-κB pathway, which provided a novel insight into the pathogenesis and treatment of RA.

The study evaluates the serum levels of Trimethylamine N-Oxide (TMAO), a gut microbial metabolite, in 286 postmenopausal women with hip fracture. From January 1, 2018 to December 31, 2018, eligible patients were included. Same women without fracture mated age were enrolled. TMAO serum levels were tested by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The serum levels of TMAO were significantly higher in patients with hip fracture than in those controls (P<0.001). The serum levels of TMAO were also higher in patients with hip fracture only than in those who also had upper limb fracture (P=0.001). High level of TMAO was proved a predictor of both hip fracture and had upper limb fracture combined hip fracture, after the adjustment of other existing risk factors [e.g., for each 1 uM increase of TMAO, odd ratio 1.16 (95% CI, 1.07-1.25), P < 0.001; and 1.12 (95% CI, 1.03-1.26), P=0.008, respectively]. In summary, increased TMAO serum levels associated with high risk of hip fracture, suggesting that increase TMAO may contribute to osteoporosis and fracture in postmenopausal women.

Objectives: This study aims to analyze the heterogeneity among different cell types in peripheral blood mononuclear cells (PBMC) in rheumatoid arthritis (RA) patients and to analyze T cell subsets to obtain key genes that may lead to RA. Materials and methods: The sequencing data of 10,483 cells were obtained from the GEO data platform. The data were filtered and normalized initially and, then, principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (TSNE) cluster analysis were performed using the Seurat package in R language to group the cells, thereby obtaining the T cells. The T cells were subjected to subcluster analysis. The differentially expressed genes (DEGs) in T cell subclusters were obtained, and the hub genes were determined by Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network construction. Finally, the hub genes were validated using other datasets in the GEO data platform. Results: The PBMC of RA patients were mainly divided into T cells, natural killer (NK) cells, B cells, and monocyte cells. The number of T cells was 4,483, which were further divided into seven clusters. The pseudotime trajectory analysis showed that the differentiation of T cells developed from cluster 0 and cluster 1 to cluster 5 and cluster 6. Through GO, KEGG and PPI analysis, the hub genes were identified. After validation by external data sets, nine genes were identified as candidate genes highly associated with the occurrence of RA, including CD8A, CCL5, GZMB, NKG7, PRF1, GZMH, CCR7, GZMK, and GZMA. Conclusion: Based on single-cell sequencing analysis, we identified nine candidate genes for diagnosing RA, and validated their diagnostic value for RA patients. Our findings may provide new sights for the diagnosis and treatment of RA.