Decoding lactylation in neuropathic pain: Immune cell infiltration patterns and machine learning-identified candidate biomarkers.

ABSTRACT: This study aimed to identify lactylation-associated genes linked to immune infiltration and diagnostic potential in neuropathic pain using integrated bioinformatic and machine learning approaches. Two microarray datasets (GSE124272 and GSE150408) comprising peripheral blood transcriptomes from 25 NP patients and 25 healthy controls were obtained from the gene expression omnibus. After batch correction and merging, the combined dataset served as the training set. Differentially expressed genes overlapping with lactylation-related gene sets were identified. Functional enrichment analyses, including gene ontology and Kyoto encyclopedia of genes and genomes pathway analyses, were performed. A protein-protein interaction network was constructed. Three machine learning algorithms-least absolute

SUBMITTER: Wu W 

PROVIDER: S-EPMC12908764 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature