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Bone & Joint Research
Vol. 12, Issue 11 | Pages 691 - 701
3 Nov 2023
Interleukin-19 promotes bone resorption by suppressing osteoprotegerin expression in BMSCs in a lipopolysaccharide-induced bone loss mouse model
Dai Z Chen Y He E Wang H Guo W Wu Z Huang K Zhao Q
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Aims

Osteoporosis is characterized by decreased trabecular bone volume, and microarchitectural deterioration in the medullary cavity. Interleukin-19 (IL-19), a member of the IL-10 family, is an anti-inflammatory cytokine produced primarily by macrophages. The aim of our study was to investigate the effect of IL-19 on osteoporosis.

Methods

Blood and femoral bone marrow suspension IL-19 levels were first measured in the lipopolysaccharide (LPS)-induced bone loss model. Small interfering RNA (siRNA) was applied to knock down IL-19 for further validation. Thereafter, osteoclast production was stimulated with IL-19 in combination with mouse macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor-κB ligand (RANKL). The effect of IL-19 was subsequently evaluated using tartrate-resistant acid phosphatase (TRAP) staining and quantitative real-time polymerase chain reaction (RT-qPCR). The effect of IL-19 on osteoprotegerin (OPG) was then assessed using in vitro recombinant IL-19 treatment of primary osteoblasts and MLO-Y4 osteoblast cell line. Finally, transient transfection experiments and chromatin immunoprecipitation (ChIP) experiments were used to examine the exact mechanism of action.

Bone & Joint Research
Vol. 9, Issue 3 | Pages 90 - 98
1 Mar 2020
An integrated analysis of the competing endogenous RNA network and co-expression network revealed seven hub long non-coding RNAs in osteoarthritis
Chen H Chen L
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Aims

This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network.

Methods

Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.

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