An Integrative analysis of single-cell RNA-seq, transcriptome and Mendelian randomization for the Identification and validation of NAD+ Metabolism-Related biomarkers in ulcerative colitis

) metabolism-related genes (NMRGs) as key genes in UC. Using the GSE87466 dataset, differentially expressed NMRGs were identified through differential expression analysis, weighted gene co-expression network analysis (WGCNA), and NMRG scoring. These NMRGs were used as exposure factors, with UC as the outcome, to identify causal candidate genes through Mendelian randomization (MR) analysis. Key genes were further validated as biomarkers using machine learning and expression validation in external datasets (GSE75214, GSE224758). A nomogram based on the expression levels of these biomarkers was constructed to predict UC risk, and the biomarkers' expression was validated through real-time quantitative polymerase chain reaction (RT-qPCR). Subsequently, signaling pathway analysis, enrichment analysis, immune infiltration analysis, and drug prediction were conducted to comprehensively understand the biological roles of the key genes in the human body. Single-cell (GSE116222) and spatial transcriptomic analyses (GSE189184) revealed the expression patterns of these key genes in specific cell types. NCF2, IL1B, S100A8, and SLC26A2 were identified as biomarkers, with NCF2 and IL1B serving as protective factors and S100A8 and SLC26A2 as risk factors for UC. The nomogram based on these biomarkers demonstrated strong predictive value. Functional analysis revealed significant IL1B, NCF2, and S100A8 enrichment in pathways such as IL-4 and IL-13 signaling, while SLC26A2 was strongly associated with respiratory electron transport. Significant differences in immune cells, such as macrophages and neutrophils, were also observed. Single-cell analysis showed high expression of NCF2, IL1B, and S100A8 in monocytes, while SLC26A2 was primarily expressed in epithelial cells, intestinal epithelial cells, and mast cells. Overall, these findings reveal the roles of NMRGs, providing valuable insights into the diagnosis and treatment of UC patients.