Identification of amino acid metabolism‑related genes as diagnostic and prognostic biomarkers in sepsis through machine learning.

Previous research has highlighted the critical role of amino acid metabolism (AAM) in the pathophysiology of sepsis. The present study aimed to explore the potential diagnostic and prognostic value of AAM-related genes (AAMGs) in sepsis, as well as their underlying molecular mechanisms. Gene expression profiles from the Gene Expression Omnibus (GSE65682, GSE185263 and GSE154918 datasets) were analyzed. Based on weighted gene co-expression network analysis and machine learning algorithms, hub AAMGs were identified in the GSE65682 database. Subsequently, hub AAMGs were evaluated for their expression levels and diagnostic and prognostic significance in sepsis, as well as their interactions with regulatory pathways and role in immune cell infiltration. Additionally, trends in AAMG expression were validated using clinical samples, and their functions in sepsis were confirmed through an model. In total, four AAMGs were identified, two of which, methionine synthase () and methionine-R-isomerase 1 (), demonstrated significant differential expression in the GSE65682, GSE185263 and GSE154918 datasets, which was further validated using clinical samples. A diagnostic nomogram based on and expression demonstrated strong diagnostic effectiveness across the three aforementioned databases. Moreover, the expression of both genes were negatively correlated with sepsis prognosis and showed stratified prognostic capabilities. Newly identified pathways included and / signaling. and negatively correlated with the infiltration of inflammatory cells, such as M1 macrophages and neutrophils, and positively correlated with anti-inflammatory cells, such as CD8 T and dendritic cells. experiments further demonstrated that overexpression of could mitigate the inhibition of cloning and proliferation induced by LPS and ATP in RAW 264.7 cells. These findings highlighted the potential of and as biomarkers for diagnosing and prognosticating sepsis, potentially acting through the regulation of methionine in the pathophysiology of this disease. The present study provided new insights into the role of AAM in the mechanisms underlying sepsis and in the potential development of future targeted therapies.