Our study employed various machine learning algorithms to identify that APLNR, PCDH12, PODXL, SLC40A1, TM4SF18, and TNFRSF25, among the lipid metabolism genes, can serve as diagnostic markers in patients with atherosclerosis and are associated with atherosclerotic immune infiltration. Here, TNFRSF25 is linked to atherosclerosis.