Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine

Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:29

Enthalten in:

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 29(2024) vom: 19., Seite 611-626

Sprache:

Englisch

Beteiligte Personen:

Kember, Rachel L [VerfasserIn]
Verma, Shefali S [VerfasserIn]
Verma, Anurag [VerfasserIn]
Xiao, Brenda [VerfasserIn]
Lucas, Anastasia [VerfasserIn]
Kripke, Colleen M [VerfasserIn]
Judy, Renae [VerfasserIn]
Chen, Jinbo [VerfasserIn]
Damrauer, Scott M [VerfasserIn]
Rader, Daniel J [VerfasserIn]
Ritchie, Marylyn D [VerfasserIn]

Themen:

Journal Article

Anmerkungen:

Date Completed 03.01.2024

Date Revised 20.03.2024

published: Print

Citation Status MEDLINE

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366509497