Both annotations and the updated LD panel improved the scores in both ancestry groups, but did not make the scores more equitable across the groups.
Abstract
Polygenic risk score (PRS) methods are evolving, and the benefit of adding functional annotations to the variant weights has been especially promising. However, less attention has been given to how the linkage disequilibrium (LD) reference panel used affects the score performance. In the current study, we compared two Bayesian approaches, one that incorporates functional annotations (LDpred-funct) and one that does not (PRS-CS), extending these applications to the hypertension (HTN) trait across two ancestry groups (European Americans EA, and African Americans, AA). In PRS-CS we used the standard HapMap 3 LD (HM3) reference panel, as well as a modified multi-ancestry reference panel (TagIt) with better coverage of variants from multiple ancestries. Individual-level data in 1,533 EA (58% with HTN) and 8,603 AA (71% with HTN) participants from the Reasons for Geographic and Racial Differences in Stroke Study (REGARDS) was used to optimize scores across the two approaches. PRS performance metrics including R2 and odds ratios (OR) per standard deviation (SD) were then used to assess PRS performance in 1,270 EA (55% with HTN) and 1,896 AA (69% with HTN) participants from the Hypertension Genetic Epidemiology Network Study (HyperGEN). Among EAs in HyperGEN we observed an R2 of 6.0% for LDpred-funct and R2 of 7.3% for PRS-CS-TagIt versus R2 of 1.4% for PRS-CS-HM3. The magnitude of the OR per SD for HTN was also higher for PRS-CS-TagIt OR=2.17 (95% CI 1.65–2.85, p = 3.0*10−8) and LDpred-funct OR=2.14 (95% CI 1.61–2.85, p = 1.46*10−7) versus PRS-CS-HM3 (OR=1.40; 95% CI 1.07–1.82, p = 1.19*10−2). Among AAs in HyperGEN, the improvements were more modest, where we observed R2 of 1.9% for LDpred-funct and R2 of 2.9% for PRS-CS-TagIt versus 0.7% for PRS-CS-HM3. We found that both annotations and the updated LD panel improved the scores in both ancestry groups, but did not make the scores more equitable across the groups.
Functional annotation-informed PRSs and expanded reference panels modestly improved prediction, particularly among EA participants, and limited performance among AA participants underscores the need for larger, more diverse genomic datasets and integrative models incorporating genetic, clinical, lifestyle, and social d...
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