Statistical analysis
T2D
REGRESSION, EVENTS, BARLOW, CVD
Descriptive data of the study participants are presented using percentages and counts for categorical variables or mean and standard deviations (SD) for quantitative traits. To identify a metabolic signature associated with the HL, a continuous HL score was associated with the final dataset of 385 metabolites (inverse-normal transformed) from the PREDIMED study at baseline used as the discovery population with a cross-validation approach. Then, data from the 1-year follow-up was used as a self-validation sample. Values missing from selected metabolites (with more than 80% of the data available) were imputed using the random forest imputation approach (“missForest” function from the “missForest” R package) as previous publications have recommended [Cox’s proportional hazards regression with Barlow weights and a robust variance estimator was used to associating HL and the metabolic signature with incident T2D and CVD risk. For each T2D and CVD nested case-cohort studies, three Cox models with different covariates were estimated with 245 events and 222 events, respectively, at baseline. The first model was adjusted for age, sex, and propensity scores (see Supplementary methods) [Several sensibility analyses were done. Participants were classified into two categories of HL score (low, < 4 points or high, ≥ 4 points) at baseline and 1-year follow-up visits, and elastic net regression models were done again (𝛼=0.6). The performance of the predictive model for the HL categorical variable was evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) generated. The sample was stratified by intervention groups designed on the PREDIMED trial (MedDiet supplemented with extra virgin olive oil, MedDiet supplemented with nuts, and control group). Associations between the high or low HL scores and the risk of developing T2D and CVD were calculated in the three intervention groups using Cox regression models with Barlow weights, and the likelihood ratio test was used to assess the significance of the 1-df interaction product-term (effect modification in multiplicative scale) between the intervention groups (MedDiet groups compared with control) and the HL metabolite profile as a categorical variable.Statistical procedures were performed with Stata 14.2 software for Windows (Stata Corp.) and R software v4.2.1 (