To refine candidate selection, we implemented machine learning algorithms (random forest and SVM-RFE) [10], which robustly identified TMCC2, TNFSF10, and CTNNA1 as key predictors of sepsis severity. The gene discussed is TMCC2; the disease is Sepsis.