Identification of basement membrane-related biomarkers associated with the diagnosis of osteoarthritis based on machine learning

Background Osteoarthritis 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.Method We 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.Result Based 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.Conclusion LAMA2 and NID2 are important potential targets for the diagnosis and treatment of OA.