Identification of iron metabolism-related key genes and exploration of their potential mechanisms in hemophagocytic lymphohistiocytosis based on transcriptome sequencing.

Background: Hemophagocytic lymphohistiocytosis (HLH) is a severe inflammatory disorder caused by excessive immune activation. This exploratory study aimed to systematically identify potential diagnostic key genes linked to iron metabolism during HLH progression using comprehensive bioinformatics analysis and explore the underlying mechanisms. Methods: Thirty peripheral blood mononuclear cell (PBMC) samples-15 from patients with HLH and 15 controls-were analyzed through mRNA sequencing. Total RNA was extracted from these samples. First, the overlap between differentially expressed genes (DEGs) and iron metabolism-related genes (FeRGs) was identified to select candidate genes. Key genes were then derived using the Boruta method and least absolute shrinkage and selection operator (LASSO) regression analysis. Further investigations, including correlation, functional, and enrichment analyses, as well as immune infiltration and drug prediction, were performed to explore the molecular mechanisms. Finally, reverse transcription quantitative PCR (RT-qPCR) was used to validate the expression levels of the key genes in clinical specimens. Results: The intersection of 464 DEGs and 520 FeRGs identified 10 candidate genes. Machine learning analysis identified ALOX15, CAT, HBZ, MT2A, and CYGB as HLH key genes. A significant positive correlation was observed between ALOX15 and HBZ, while ALOX15 showed a notable negative correlation with CYGB and MT2A (|correlation coefficient (r)| > 0.3, Conclusion: This study identified five validated key genes-ALOX15, CAT, HBZ, MT2A, and CYGB-offering new insights into HLH pathogenesis and potential therapeutic targets.