Identification of mitophagy-related subgroups and biomarker in AIS osteopenia based on bioinformatics and machine learning approaches

Abstract

Abstract Background: Adolescent idiopathic scoliosis (AIS) is a complicated spinal deformity with an unknown origin. The progression of AIS and the severity of spinal curvature are both substantially linked to osteopenia. Mitophagy is critical for the balance of osteogenic and osteoclastic development in BMSCs, but its significance in AIS osteopenia is unknown. The goal of this work was to look into the mechanism of mitophagy in AIS osteopeniapatients' BMSCs and give a new diagnostic and therapeutic target for AIS osteopenia. Methods: The gene expression profiles of BMSCs from AIS patients are available in the Gene Expression Omnibus (GEO) collection. Consensus cluster analysis of mitophagy-related genes was used to identify molecular isoforms.Using machine learning, identify mitophagy-related diagnostic indicators of osteopenia in AIS. The biological function and immunological features of diagnostic biomarkers were then assessed using GSEA and ssGSEA. Results: Immune cell infiltration was found to differ between mitophagy-related subtypes, implying that the development of AIS osteopenia may be associated with immune cell infiltration. UBA52 was identified as the best mitophagy-related diagnostic biomarker for osteopenia in AIS by machine learning methods, and GSEA revealed that UBA52 mostly affected osteopenia in AIS through oxidative phosphorylation. In addition, UBA52 regulates immune cell infiltration and may contribute to osteopenia in AIS patients. Conclusion: According to our findings, AIS patients can be split into two mitophagy subgroups. Furthermore, we used machine learning to identify UBA52, a mitophagy-related diagnostic marker, and discovered that UBA52 played a significant role in increasing osteopenia in AIS.