ArticleBMC medical genomics2023
Identification of basement membrane-related biomarkers associated with the diagnosis of osteoarthritis based on machine learning.
Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Muscle transcriptome profiling reveals novel molecular pathways and biomarkers in laminin-α2 deficient patients.Acta neuropathologica communications · 2026Article
- Sex differences in the pathogenesis of degenerative knee osteoarthritis: a comparative transcriptomics analysis.Frontiers in aging · 2026Article
- Identification of Key Glycolysis-Related Genes in Osteoarthritis and Their Correlation with Immune Infiltration Using Bioinformatics Analysis and Machine Learning.Open access rheumatology : research and reviews · 2025Article
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Authors and funding
9 authors.
Funding
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Abstract
backgroundOsteoarthritis is a very common clinical disease in middle-aged and elderly individuals, and with the advent of ageing, the incidence of this disease is gradually increasing. There are few studies on the role of basement membrane (BM)-related genes in OA.
methodWe used bioinformatics and machine learning methods to identify important genes related to BMs in OA patients and performed immune infiltration analysis, lncRNA‒miRNA-mRNA network prediction, ROC analysis, and qRT‒PCR.
resultBased on the results of machine learning, we determined that LAMA2 and NID2 were the key diagnostic genes of OA, which were confirmed by ROC and qRT‒PCR analyses. Immune analysis showed that LAMA2 and NID2 were closely related to resting memory CD4 T cells, mast cells and plasma cells. Two lncRNAs, XIST and TTTY15, were simultaneously identified, and lncRNA‒miRNA‒mRNA network prediction was performed.
conclusionLAMA2 and NID2 are important potential targets for the diagnosis and treatment of OA.
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