ArticleFrontiers in pharmacology2024
Integrated analysis of genes shared between type 2 diabetes mellitus and osteoporosis.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Cellular signaling crosstalk between osteoporosis and diabetes: Common mechanisms and therapeutic targets (Review).Biomedical reports · 2026Review
- The association between the ZJU index and bone mineral density (BMD) among patients with type 2 diabetes mellitus.Metabolism open · 2025Article
- Emerging applications of feature selection in osteoporosis research: from biomarker discovery to clinical decision support.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2025Review
- Identification of retinol dehydrogenase 10 as a shared biomarker for metabolic dysfunction-associated steatotic liver disease and type 2 diabetes mellitus.Frontiers in pharmacology · 2025Article
- Association between C-reactive protein-triglyceride glucose index and abnormal BMD in middle-aged and elderly patients with type 2 diabetes mellitus: a cross-sectional study.Frontiers in medicine · 2025Article
- The impact of diabetes mellitus on tendon pathology: a review.Frontiers in pharmacology · 2024Review
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7 authors.
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Abstract
Background: The relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OP) has been widely recognized in recent years, but the mechanism of interaction remains unknown. The aim of this study was to investigate the genetic features and signaling pathways that are shared between T2DM and OP. Methods: We analyzed the GSE76894 and GSE76895 datasets for T2DM and GSE56815 and GSE7429 for OP from the Gene Expression Omnibus (GEO) database to identify shared genes in T2DM and OP, and we constructed coexpression networks based on weighted gene coexpression network analysis (WGCNA). Shared genes were then further analyzed for functional pathway enrichment. We selected the best common biomarkers using the least absolute shrinkage and selection operator (LASSO) algorithm and validated the common biomarkers, followed by RT-PCR, immunofluorescence, Western blotting, and enzyme-linked immunosorbent assay (ELISA) to validate the expression of these hub genes in T2DM and OP mouse models and patients. Results: We found 8,506 and 2,030 DEGs in T2DM and OP, respectively. Four modules were identified as significant for T2DM and OP using WGCNA. A total of 19 genes overlapped with the strongest positive and negative modules of T2DM and OP. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed these genes may be involved in pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin system signaling pathway. The LASSO algorithm calculates the six optimal common biomarkers. RT-PCR results show that Conclusion: Based on the WGCNA and LASSO algorithms, we identified genes and pathways that were shared between T2DM and OP. Both pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin systems may be associated with the pathogenesis of T2DM and OP. Moreover,
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