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

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

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.

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心脏代谢特征的多基因风险评分显示了祖先对于预测性精准医疗的重要性。
多基因风险评分(PRS)主要来源于欧洲血统(EUR)个体的全基因组关联研究(GWAS)。在这项研究中,我们在宾夕法尼亚大学医学生物库(PMBB)中对基于多祖先GWAS的五种心脏代谢表型的PRS进行了深入评估,随后进行了全表型关联研究(PheWAS)。我们检查了所有个体的PRS表现,并分别在非洲血统(AFR)和欧洲血统群体。对于AFR个体,使用多祖先LD面板得出的PRS对5个PRS中的4个(舒张压、收缩压、T2D和BMI)的效应值高于来自AFR LD面板的效应值。相比之下,对于欧洲个体,与欧洲LD面板相比,多祖先LD面板PRS对五分之二的PRS (SBP和T2D)显示出更高的效应量。这些发现强调了在不同遗传背景下利用多祖先LD面板进行PRS衍生的潜在好处,并证明了所有个体的总体稳健性。我们的研究结果还揭示了PRS与各种表型类别之间的显著关联。例如,CAD PRS在AFR中与18种表型相关,在EUR中与82种表型相关,而T2D PRS在AFR中与84种表型相关,在EUR中与78种表型相关。值得注意的是,在AFR组和EUR组的不同PRSs中观察到高脂血症、肾衰竭、心房颤动、冠状动脉粥样硬化、肥胖和高血压等关联,其效应大小和显著性水平各不相同。然而,在AFR个体中,与EUR个体相比,PRS与其他表型的关联强度和数量普遍降低。我们的研究强调了未来的研究需要优先考虑:1)在不同的祖先群体中进行GWAS; 2)创建一个普遍适用于所有遗传背景的世界性PRS方法。这些进步将促进更加公平和个性化的精准医疗方法。
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Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface. Session Introduction: Overcoming health disparities in precision medicine: Intersectional approaches in precision medicine. Session Introduction: Precision Medicine: Multi-modal and multi-scale methods to promote mechanistic understanding of disease. Social risk factors and cardiovascular risk in obstructive sleep apnea: a systematic assessment of clinical predictors in community health centers. A Visual Analytics Framework for Assessing Interactive AI for Clinical Decision Support.
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