Abstract
AIM: Fatty acid metabolism is pivotal for lipid synthesis, cellular signaling, and maintaining cell membrane integrity. However, its diagnostic significance in type 2 diabetes mellitus (T2DM) remains unclear. MATERIALS AND METHODS: Three datasets and fatty acid metabolism-related genes were retrieved. Differential expression analysis, WGCNA, machine learning algorithms, diagnostic analysis, and validation were employed to identify key feature genes. Functional analysis, ceRNA network construction, immune microenvironment assessment, and drug prediction were conducted to explore the underlying molecular mechanisms. RESULTS: Six feature genes were identified with strong diagnostic performance and were involved in processes such as ribosome function and fatty acid metabolism. Immune cells, including dendritic cells, eosinophils, and neutrophils, may play a role in the progression of T2DM. ceRNA and drug-target network analysis revealed potential interactions, such as RP11-miR-29a-YTHDF3 and BPA-MSANTD1. The expression patterns of the feature genes, except for YTHDF3, were consistently upregulated in T2DM, aligning with trends observed in the training set. CONCLUSION: This study investigated the potential molecular mechanisms of six fatty acid metabolism-related genes in T2DM, offering valuable insights that may guide future research and therapeutic development.