Subsequently, we identified the final six feature variables (RNF5, UBAC2, DNAJC10, RNF103, DDX3X, and NGLY1) via intersecting the results of SVM and LightGBM machine learning models, all of which could accurately predict the progression of AD. The gene discussed is UBAC2; the disease is Alzheimer disease.