Identification of transcription factors and construction of a novel miRNA regulatory network in primary osteoarthritis by integrated analysis

Jiang, Ying; Shen, Yi; Ding, Liyan; Xia, Shuhua; Jiang, Liying

doi:10.1186/s12891-021-04894-2

Cited by 8 publications

(3 citation statements)

References 47 publications

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“…In the present study, the PPI network map of the SIN for the treatment of OA was constructed using String database and Cytoscape software, and 16 underlying core targets, including ALB, IGF1, RXRA, MMP9, PPARG, PTGS2, CTSK, NR3C1, AR, BMP2, CYP2C9, ESR1, ESR2, HSD11B1, MMP1, and TGFBR1, were acquired. Among them, ALB, IGF1, RXRA, MMPs, PPARG, PTGS2, ESRs, CTSK, TGFBR1, NR3C1, and BMP2 genes are positively involved in the OA disease, [25][26][27][28][29][30][31][32] while CYP2C9 and HSD11B1 genes take parts in the inflammatory response. 33,34 The results indicated that these 16 major genes are potential core targets responsible for SIN to treat OA, and are closely associated with inflammatory response.…”

Section: Discussionmentioning

confidence: 99%

Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis

Wang,

Lai,

Xiang

et al. 2024

Natural Product Communications

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Objective To systematically explore the targets and signaling pathways of sinomenine (SIN) in the treatment of osteoarthritis (OA) using integrated network pharmacology, molecular docking, and experimental validation. Methods The TCMSP, SwissADME, and Pharmmapper databases were used to predict SIN targets, while the databases of GeneCards, DisGeNET, OMIM, and DrugBank were selected to acquire OA targets. Subsequently, the intersection targets of SIN and OA disease were collected using the Veeny platform. Then, the protein-protein interaction (PPI) network map of “SIN-targets-OA” was established using String database and Cytoscape software. Additionally, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). Additionally, the potential proteins of SIN against OA were validated via molecular docking technique. Finally, the experimental validation was performed in SW1353 cells induced by interleukin (IL)-1β. Results A total of 315 potential targets of SIN and 4300 OA-associated targets were collected from public databases, and 42 intersecting potential targets of SIN and OA disease acquired. Then, the PPI network diagram of “SIN-targets-OA” was acquired that comprised a total of 43 nodes and 82 edges. Moreover, 173 GO and 21 KEGG pathway entries were screened with a P-value <.05. Among them, peroxisome proliferator-activated receptor (PPAR) and IL-17 are the core signaling pathways. Molecular docking technique indicated strong binding energies of SIN with PPAR (−6.1 kcal/mol) and IL-17 (−6.3 kcal/mol). Lastly, SIN at the concentration of 50 μmol/L has a significant effect on IL-1β-induced SW1353 cells by the inhibition of PPAR-γ and IL-17A proteins without cytotoxicity. Conclusion This work revealed the underlying targets and signaling pathways of SIN against OA using integrated network pharmacology molecular docking, and experimental validation. These findings provide scientific evidence for the clinical application of SIN for OA treatment.

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Section: Discussionmentioning

confidence: 99%

Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis

Wang,

Lai,

Xiang

et al. 2024

Natural Product Communications

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“…MiRNAs control the outflow of target qualities by base blending to integral locales in the 3ʹ-untranslated district (3ʹ-UTR) of target mRNAs and lead to translational suppression or the debasement of the mRNAs [ 5 ]. An enormous number of past examinations have revealed that different miRNAs are involved in controlling the etiology of musculoskeletal disorders [ 6 – 8 ]. Lorenzo Giordano et al [ 9 ] found that multiple miRNAs were involved in the process of tendon lesions by searching multiple databases, but the use of siRNA has a very important effect on rheumatoid arthritis, tendon regeneration, and healing [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

MiR-320a upregulation improves IL-1β-induced osteoarthritis via targeting the DAZAP1 and MAPK pathways

Mao

Zhang

2023

J Orthop Surg Res

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Purpose Osteoarthritis (OA), a constant illness described by articular cartilage degeneration, usually manifested by joint pain and helpless development. Numerous literatures suggest that microRNAs play an important regulatory role in OA, yet the role of miR-320a in OA remains largely obscure. Materials and methods To evaluate the expression of miR-320a mRNA, quantitative real-time polymerase chain reaction was used. Cell counting kit-8 assay, Edu staining, Annexin V-FITC/PI apoptosis detection assay, Caspases 3 staining, and trypan staining were conducted to monitor cell proliferation and apoptosis. Western blot was applied to examine DAZAP1 and ERK/JNK/MAPK associated protein expression. Luciferase reporter gene experiments were performed to confirm the relationships between miR-320a and DAZAP1. ELISA assay was adopted to analyze the secretion of inflammation cytokines IL-6, IL-8, and TNF-α. Results In an in vitro osteoarthritis model caused by IL-1β, miR-320a expression was markedly reduced. Overexpression of miR-320a restored IL-1β-inhibited chondrocyte proliferation, induced apoptosis and inflammatory response. Mechanistically, miR-320a affected HC-A cell proliferation, apoptosis and inflammatory response by regulating DAZAPI. Meanwhile, the ERK/JNK/MAPK pathway is also involved in the regulatory role of miR-320a on OA. Conclusion Our results show an important role for miR-320a and provide new therapeutic targets for avoiding and treating osteoarthritis.

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“…Recent sequencing studies in blood identified differentially expressed microRNAs in OA versus controls and in early-stage versus late-stage radiographic knee OA. 7 – 10 Among these, a well-powered study revealed a signature of seven circulating microRNAs to be associated with early-stage radiographic knee OA. 8 However, sequencing remains to be applied to large-scale longitudinal cohorts to identify microRNAs that are associated with disease progression.…”

Section: Introductionmentioning

confidence: 99%

Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort

Ali

Espin‐Garcia

Wong

et al. 2022

Therapeutic Advances in Musculoskeletal

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Introduction: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. Methods: Participants with Kellgren–Lawrence (KL) grade 0/1 at baseline were included ( N = 106). Fast-progressors were defined by an increase to KL 3/4 by 4-year follow-up ( N = 20), whereas slow-progressors showed an increase to KL 2/3/4 only at 8-year follow-up ( N = 35). Non-progressors remained at KL 0/1 by 8-year follow-up ( N = 51). MicroRNA-sequencing was performed on plasma collected at baseline and 4-year follow-up from the same participants. Negative binomial models were fitted to identify differentially expressed (DE) microRNAs. Penalized logistic regression (PLR) analyses were performed to select combinations of DE microRNAs that distinguished fast-progressors. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate predictive ability. Results: DE analyses revealed 48 microRNAs at baseline and 2 microRNAs at 4-year follow-up [false discovery rate (FDR) < 0.05] comparing fast-progressors with both slow-progressors and non-progressors. Among these were hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e, which were predicted to target gene families, including members of the 14-3-3 gene family, involved in signal transduction. PLR models included miR-320 members as top predictors of fast-progressors and yielded AUC ranging from 82.6 to 91.9, representing good accuracy. Conclusion: The miR-320 family is associated with fast-progressing radiographic knee OA and merits further investigation as potential biomarkers and mechanistic drivers of knee OA.

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Identification of transcription factors and construction of a novel miRNA regulatory network in primary osteoarthritis by integrated analysis

Cited by 8 publications

References 47 publications

Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis

Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis

MiR-320a upregulation improves IL-1β-induced osteoarthritis via targeting the DAZAP1 and MAPK pathways

Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort

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