INS and Obesity: In contrast to a model including obesity-related standard clinical measures (that is, ordinary least squares (OLS) linear regression model with sex, age, triglycerides, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, glucose, insulin and homeostatic model assessment for insulin resistance (HOMA-IR) as regressors; StandBMI model), each omics-based model demonstrated significantly higher performance in BMI prediction, ranging from out-of-sample R2 = 0.48 (ChemBMI) to 0.70 (ProtBMI) compared to 0.37 (StandBMI) (Fig. 1c).