Abstract P491: Functional Annotations for Improvements in Height and Blood Pressure Polygenic Risk Scores

Background: Genome-wide association studies (GWAS) have advanced our understanding of the polygenic basis of common, complex disorders. However, translating GWAS findings into clinical applications remains challenging. Polygenic risk scores (PRS) hold promise for clinical use with recent methodologies enhancing predictive accuracy. This study compared two PRS (LDpred-funct which incorporates functional annotations into the score and a traditional linear scoring system) for traits with varying heritability in European- (EA) and African-ancestry (AA) populations, addressing a need to evaluate novel approaches across diverse conditions and populations. Hypothesis: This study hypothesized that integrating functional annotations into PRS derivation will enhance performance compared to assessing the genetic load for a trait. The addition will provide improvement for (1) traits with high (height) compared to moderate (systolic blood pressure, SBP) heritability and (2) individuals with EA relative to AA. Methods: This study used multi-ancestry summary statistics representing data from 4,080,687 individuals for height (GIANT consortium) and 436,099 individuals for SBP adjusted for antihypertensive medication use (UK Biobank). Two PRS for these traits were constructed using LDpred-funct: PRS funct which incorporates the functional annotation and PRS raw which is a simple linear scoring system. Optimization was performed in 8,916 AA and 1,716 EA participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. PRS predictive performance was evaluated by calculating the proportion of trait variance explained by the PRS (R 2 ) after accounting for age, sex, and genetic ancestry. Results: For height, the PRS funct outperformed PRS raw among both race groups, with a greater improvement among EA (PRS funct R 2 =0.110 versus PRS raw R 2 =0.060, 5% difference) compared to AA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.034, 0.8% difference). Similar findings were observed for medication-adjusted SBP, where PRS funct had better predictive performance than PRS raw , and with greater improvement observed in the EA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.027, 1.5% difference) compared to AA participants (PRS funct R 2 =0.014 versus PRS raw R 2 =0.010, 0.4% difference). Conclusions: Incorporating functional priors into the PRS enhanced the predictive accuracy for both traits. A greater improvement was observed for the higher heritability (height) versus the moderate heritability (SBP) trait, as well as within individuals of EA compared to AA. These findings are currently undergoing validation, using data from the Electronic Medical Records and Genomics (eMERGE) Network, highlighting the potential of incorporating functional annotations into PRS development for broader clinical applications.