Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for...

Nonspecific orbital inflammation (NSOI), also known as idiopathic orbital inflammation, comprises a heterogeneous group of immune-mediated disorders affecting orbital tissues, unified by the absence of a defined etiology. Lactotransferrin (LTF), an iron-binding glycoprotein, exerts potent antimicrobial activity by sequestering iron essential for microbial growth, and demonstrates broad-spectrum antibacterial, antiviral, and antifungal properties.

LTF was identified through the intersection analysis of common DEGs from datasets GSE58331 and GSE105149 from the GEO database, alongside immune-related gene lists from the ImmPort database, using Multiple Machine learning and WGCNA analysis. GSEA and GSVA were conducted with gene sets co-expressed with LTF. To further investigate the correlation between LTF and immune-related biological processes, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate immune microenvironment characteristics of each sample. The expression levels of LTF were subsequently validated using GSE105149.

Lasso and SVM-RFE algorithms pinpointed 28 hub genes. Enrichment analysis revealed that gene sets positively correlated with LTF were enriched in immune-related pathways. For biological function analysis in LTF, retina homeostasis, sensory perception of bitter taste, and tissue homeostasis were emphasized. Immune infiltration analysis indicated that Plasma cells and B cells naive were positively associated (That is, when the expression level of LTF increases, these immune cells also increase accordingly) with LTF, whereas B cells memory, Macrophages M2, Mast cells resting, Monocytes, NK cells activated, T cells regulatory (Tregs) were negatively associated with LTF. LTF demonstrated significant diagnostic potential in differentiating NSOI.

This study identifies LTF as a potential biomarker linked to NSOI, providing insights into its pathogenesis and offering new avenues for tracking disease progression.