LASSO regression was used to select predictive factors, employing ten-fold cross-validation and a minimization criterion to determine the optimal coefficient λ, which led to the selection of nine non-zero coefficient predictive variables, including hyperlipidemia, sleep disorders, MMT score, NIHSS score, location of occlusion, CRP, ALB, FBG, and CK (Figure 2a and 2b). The gene discussed is CRP; the disease is hyperlipidemia.