ArticleAging2024
Identification of biomarkers and immune infiltration characterization of lipid metabolism-associated genes in osteoarthritis based on machine learning algorithms.
Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Integration of Single-cell Sequencing Analysis Reveals Disulfidptosis Related Molecular Subtype and Novel Prognosis System for Osteosarcoma.Current medicinal chemistry · 2026Article
- Article
- Network toxicology and immune-metabolic dysregulation: linking per- and polyfluoroalkyl substances exposure to osteoarthritis pathogenesis.Toxicology research · 2025Article
- Associations between surrogate insulin resistance indexes and osteoarthritis: NHANES 2003-2016.Scientific reports · 2025Article
- Intermittent fasting in osteoarthritis: from mechanistic insights to therapeutic potential.Frontiers in nutrition · 2025Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteoarthritis (OA) is a prevalent degenerative condition commonly observed in the elderly, leading to consequential disability. Despite notable advancements made in clinical strategies for OA, its pathogenesis remains uncertain. The intricate association between OA and metabolic processes has yet to receive comprehensive exploration. In our investigation, we leveraged public databases and applied machine learning algorithms, including WGCNA, LASSO, RF, immune infiltration analysis, and pathway enrichment analysis, to scrutinize the role of lipid metabolism-associated genes (LAGs) in the OA. Our findings identified three distinct biomarkers, and evaluated their expression to assess their diagnostic value in the OA patients. The exploration of immune infiltration in these patients revealed an intricate relationship between immune cells and the identified biomarkers. In addition,
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Registered trials
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