The entire process harnessed multiple machine learning algorithms to elucidate the fundamental signature genes intrinsic to atherosclerosis, ultimately pinpointing CD36, S100A10, and CSNK1A1 as genetically correlated markers. The gene discussed is CD36; the disease is atherosclerosis.