This study determined novel metabolism-related diagnostic biomarkers for ulcer­ative colitis (UC) and assessed their correlation with immune cell infiltration levels. Transcriptome data of UC was downloaded from the Gene Expression Omnibus (GEO) database, metabolism-related genes were summarised from the Gene Set Enrichment Analysis (GSEA) database. A total of 537 metabolism-related differen­tially expressed genes (DEGs) in UC were applied to functional enrichment analy­sis. We processed least absolute shrinkage and selection operator (LASSO) regres­sion analysis and support vector machine-recursive feature elimination (SVM-RFE). We obtained 6 potential metabolism-related diagnostic biomarkers (CHST13, ETNK1, LPCAT1, PDE6A, PLA2G2A, and UGT2A3). Expression patterns and diagnostic ROC curves were depicted in both the training and testing co­horts to verify their diagnostic value. Immune infiltration analysis indicated that UC samples have more abundant infiltration levels of immune cells. Fur­thermore, the upregulated diagnostic biomarkers significantly positively cor­related with B cell memory, T cell CD4 memory activated, dendritic cells ac­tivated, etc., while the downregulated ones mainly significantly positively correlated with mast cells resting, NK cells activated, and macrophages M2. Our study primarily identified 6 metabolism regulators (CHST13, ETNK1, LP­CAT1, PDE6A, PLA2G2A, and UGT2A3) as potential diagnostic biomarkers for UC and determined their correlation with immune infiltration.