ArticleAnnals of translational medicine2021
Identifying a possible new target for diagnosis and treatment of postmenopausal osteoporosis through bioinformatics and clinical sample analysis.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Three-Dimensionally Printed Scaffolds and Drug Delivery Systems in Treatment of Osteoporosis.Biomimetics (Basel, Switzerland) · 2025Review
- MIR155HG suppresses the osteogenic differentiation of bone marrow mesenchymal stem cells through regulating miR-155-5p and DKK1 expression.Journal of orthopaedic surgery and research · 2025Article
- Comparison between Two Different Synthesis Methods of Strontium-Doped Hydroxyapatite Designed for Osteoporotic Bone Restoration.Materials (Basel, Switzerland) · 2024Article
- Long non-coding RNA Homeobox D gene cluster antisense growth-associated long noncoding RNA/microRNA-182-5p/Homeobox protein A10 alleviates postmenopausal osteoporosis via accelerating osteoblast differentiation of bone marrow mesenchymal stem cells.Journal of orthopaedic surgery and research · 2023Article
- Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis.Aging · 2023Article
- Construction of ceRNA regulatory networks for osteoporosis.Molecular medicine reports · 2023Article
- GATA4-activated lncRNA MALAT1 promotes osteogenic differentiation through inhibiting NEDD4-mediated RUNX1 degradation.Cell death discovery · 2023Article
- Identification of mitophagy-related biomarkers in human osteoporosis based on a machine learning model.Frontiers in physiology · 2023Article
- Bioinformatics analysis identification ofExperimental and therapeutic medicine · 2022Article
- Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis.Annals of translational medicine · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPostmenopausal osteoporosis, a common yet chronic systemic metabolic disease, has become a major public health problem due to life expectancy increasing around the world. The differentiation of mesenchymal stem cells (MSCs) into osteoblasts, and the differentiation of circulating monocyte cells into osteoclasts, play an important role in the balance of bone metabolism. However, when both undergo pathological changes, it can lead to abnormalities, resulting in osteoporosis. This study aims to explore a new biomarker for postmenopausal osteoporosis, thereby providing a new entry point for bioinformatic research into the clinical diagnosis and treatment of the disease.
methodsUsing the Gene Expression Omnibus (GEO) database, microarray analysis was conducted to identify differentially expressed genes in MSCs and monocytes in both postmenopausal osteoporosis patients and a healthy control group. The Database for Annotation, Visualization and Integrated Discovery (DAVID) database was used to analyze the function and enrichment of the selected genes, and a protein-protein interaction (PPI) network was constructed from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website and displayed in Cytoscape. To achieve the final results, module analysis of the PPI network was performed by using Molecular Complex Detection (MCODE).
resultsWe identified 45 high-expression and 26 low-expression genes through the study, all of which underwent pathway enrichment analysis. This enrichment was observed in the cell cycle regulation, osteoclast differentiation, tumor necrosis factor (TNF) signaling pathway, and RNA transport. The top 10 hub genes of the PPI network were
conclusionsThrough bioinformatic analysis and clinical specimen validation, our study provides a new way for exploring the pathogenesis of postmenopausal osteoporosis. Most importantly, it suggests that the hub genes,
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