Figure 1: Study design.

Panel a: the proposed ensemble model framework. The ensemble is composed of two models. The baseline model, trained on covariates $\left(X_b\right)$ only for prediction of SBP and DBP $\left({\hat{y}}_b\right)$. To assess the accuracy of the baseline model we calculated the residuals (baseline residuals $r_b$) by subtracting the predicted value of SBP/DBP from the actual value of SBP/DBP. The genetic model was trained on a subset of the covariates, and genetic components (global PRSs) for prediction of the baseline model residuals $r_b$. We measured the accuracy of the genetic model by subtracting predicted genetic residuals ${\hat{r}}_g$ from baseline residuals $r_b$. The overall prediction of BP by the ensemble model is the sum of the predicted baseline BP ${\hat{y}}_b$ (by the baseline model) and the predicted baseline residuals ${\hat{r}}_b$ (by the genetic model). The accuracy of the ensemble model was assessed by calculating percent variance explained (PVE) by two models jointly. Panel b: the split of the primary, TOPMed dataset, into training and testing sets followed by the 5-fold cross validation procedure where the training dataset is further split into 5 equal parts with one part designated for testing (repeated 5 times with 1/5 of the training data being designated at random for testing at each iteration). Panel c: increasing levels of genetic models’ complexity where each new model included additional PRSs. Panel d: the process of calculating local PRSs per LD-blocks (secondary analysis).

BBJ: BioBank Japan. BP: blood pressure. GWAS: genome wide association study. LD: linkage disequilibrium. Level: model complexity level. MVP: Million Veteran Program. P: p-value threshold. PRS: polygenic risk score. SNPs: single-nucleotide polymorphisms. TOPMed: Trans-Omics for Precision Medicine project. UKBB+ICBP: UK Biobank and International Consortium for Blood Pressure.