遗传谱系
多基因风险评分
人口
全基因组关联研究
修剪
生物
人口学
医学
单核苷酸多态性
遗传学
基因型
基因
社会学
农学
作者
Johanna L. Smith,Catherine Tcheandjieu,Ozan Dikilitas,Kruthika Iyer,Kazuo Miyazawa,Austin T. Hilliard,Julie A. Lynch,Jerome I. Rotter,Yii‐Der Ida Chen,Wayne Huey Herng Sheu,Kyong–Mi Chang,Stavroula Kanoni,Phil Tsao,Shefali S. Verma,Matthew Kosel,Sue Clarke,Daniel J. Schaid,Themistocles L. Assimes,Iftikhar J. Kullo
出处
期刊:Circulation
[Ovid Technologies (Wolters Kluwer)]
日期:2024-02-21
被引量:1
标识
DOI:10.1161/circgen.123.004272
摘要
Background: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRS CHD ) for 5 genetic ancestry groups. Methods: We derived ancestry-specific and multi-ancestry PRS CHD based on pruning and thresholding and continuous shrinkage priors (polygenic risk score for CHD developed using ancestry-based continuous shrinkage methods) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRS CHD in 176 988 individuals across 9 diverse cohorts. Results: Multi-ancestry polygenic risk score for CHD developed using pruning and thresholding methods and polygenic risk score for CHD developed using ancestry-based continuous shrinkage methods outperformed ancestry-specific Polygenic risk score for CHD developed using pruning and thresholding methods and polygenic risk score for CHD developed using ancestry-based continuous shrinkage methods across a range of tuning values. Two best-performing multi-ancestry PRS CHD (ie, polygenic risk score for CHD developed using pruning and thresholding methods optimized using a multi-ancestry population and polygenic risk score for CHD developed using ancestry-based continuous shrinkage methods optimized using a multi-ancestry population) and 1 ancestry-specific (PRS CSxEUR ) were taken forward for validation. Polygenic risk score for CHD developed using pruning and thresholding methods (PT) optimized using a multi-ancestry population demonstrated the strongest association with CHD in individuals of South Asian genetic ancestry and European genetic ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41–3.14], 1.65 [1.59–1.72]), followed by East Asian genetic ancestry (1.56 [1.50–1.61]), Hispanic/Latino genetic ancestry (1.38 [1.24–1.54]), and African genetic ancestry (1.16 [1.11–1.21]). Polygenic risk score for CHD developed using ancestry-based continuous shrinkage methods optimized using a multi-ancestry population showed the strongest associations in South Asian genetic ancestry (2.67 [2.38–3.00]) and European genetic ancestry (1.65 [1.59–1.71]), lower in East Asian genetic ancestry (1.59 [1.54–1.64]), Hispanic/Latino genetic ancestry (1.51 [1.35–1.69]), and the lowest in African genetic ancestry (1.20 [1.15–1.26]). Conclusions: The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRS CHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African genetic ancestry. This highlights the need for larger Genome-wide association study datasets of underrepresented populations to enhance the performance of PRS CHD .
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