Fig. 1

Study design and the workflow of building a BLDM model. Upon patient admission, clinical information was collected, and peripheral blood was obtained for RRBS. A discovery cohort included 59 BTNs and 49 MTNs. Differential leukocyte DNA methylation between MTNs and BTNs were identified, and methylation features were selected to develop a methylation model. The performance of multiple methylation models was compared, and the optimal RF model was selected as the final model and named the BLDM model. The principle of the RF model was shown in the diagram, incorporating a total of 60 MHB biomarkers into the model. The model output methylation scores. The validation cohort comprised 55 cases of BTN and 42 cases of MTN. An independent test cohort consisted of 53 BTNs and 35 MTNs. The performance of the BLDM model was assessed, the correlation between the methylation scores and the benign/malignant nature was analyzed, the performance of the BLDM model in ACR TI-RADS category 4 and 5, and its performance in both micronodules and non-micronodules was assessed. TN, thyroid nodule; BTN, benign thyroid nodule; MTN, malignant thyroid nodule; RRBS, reduced representation bisulfite sequencing; DMR, differential methylation region; MHB, methylation haplotype block; RF, random forest