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利用遗传血统连续信息对混合人群的多基因风险评分进行插值。

Leveraging genetic ancestry continuum information to interpolate PRS for admixed populations.

作者信息

Ruan Yunfeng, Bhukar Rohan, Patel Aniruddh, Koyama Satoshi, Hull Leland, Truong Buu, Hornsby Whitney, Zhang Haoyu, Chatterjee Nilanjan, Natarajan Pradeep

机构信息

Program in Medical and Population, Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA.

Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.

出版信息

medRxiv. 2025 Jan 14:2024.11.09.24316996. doi: 10.1101/2024.11.09.24316996.

Abstract

The relatively low representation of admixed populations in both discovery and fine-tuning individual-level datasets limits polygenic risk score (PRS) development and equitable clinical translation for admixed populations. Under the assumption that the most informative PRS weight for a homogeneous sample varies linearly in an ancestry continuum space, we introduce a Genetic tance-assisted PRS mbination Pipeline for erse Genetic ncestrie () to interpolate a harmonized PRS for diverse, especially admixed, ancestries, leveraging multiple PRS weights fine-tuned within single-ancestry samples and genetic distance. DiscoDivas treats ancestry as a continuous variable and does not require shifting between different models when calculating PRS for different ancestries. We generated PRS with DiscoDivas and the current conventional method, i.e. fine-tuning multiple GWAS PRS using the matched or similar ancestry samples. DiscoDivas generated a harmonized PRS of the accuracy comparable to or higher than the conventional approach, with the greatest advantage exhibited in admixed individuals.

摘要

在发现和微调个体水平数据集方面,混合人群的代表性相对较低,这限制了多基因风险评分(PRS)的发展以及混合人群公平的临床转化。假设同质样本中最具信息性的PRS权重在祖先连续统空间中呈线性变化,我们引入了一种用于不同遗传祖先的遗传距离辅助PRS组合管道(DiscoDivas),以利用在单一祖先样本中微调的多个PRS权重和遗传距离,为不同的,特别是混合的祖先插值一个统一的PRS。DiscoDivas将祖先视为一个连续变量,在为不同祖先计算PRS时不需要在不同模型之间切换。我们使用DiscoDivas和当前的传统方法(即使用匹配或相似祖先样本微调多个GWAS PRS)生成了PRS。DiscoDivas生成的统一PRS准确性与传统方法相当或更高,在混合个体中表现出最大优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfe7/11759244/ceb9c9742618/nihpp-2024.11.09.24316996v2-f0001.jpg

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