A total of 32 potential variables in Table 1 were analyzed by random forest, of them, 9 variables (postprandial blood glucose, smoking status, peripheral neuropathy, fast blood-glucose, carotid atherosclerosis, occupation, education attainment, high sensitivity c-reactive protein (hsCRP), and hypertension) with Mean Decrease Accuracy value > 0.5 were included in the prediction model, and the AUC was 69.2% (Fig. 3). This evidence concerns the gene CRP and carotid atherosclerosis.