美国约翰霍普金斯大学彭博公共卫生学院Nilanjan Chatterjee和美国国立癌症研究院Haoyu Zhang课题组合作提出，跨人种多基因预测新方法可提高在不同人群的适应性。相关论文于2023年9月25日发表于国际学术期刊《自然-遗传学》杂志上。
研究人员研发了CT-SLEB，这是一种强大且可扩展的多基因风险评分（PRS）计算方法，它使用来自多人群训练样本的人种特异性全基因组关联研究汇总统计数据，并整合聚集和阈值，运用经验贝叶斯定律和超级学习。
研究通过大规模模拟全基因组关联研究（1900 万个常见变异）和 23个数据库、Me, Inc.、全球脂质遗传学联盟、All of Us 和英国生物银行的数据集评估了 CT-SLEB 和 9 种替代方法，涉及 510 万不同人种的个体，其中 118 万个体来自四个非欧洲人群，包括13个复杂性状。结果表明，与简单的替代方案相比，CT-SLEB显著提高了非欧洲人群的PRS表现，其性能与最近的计算密集型方法相当甚至更好。
此外，该模拟研究为样本量和SNP密度对多血统风险预测的影响提供了的见解。
研究人员表示，PRS越来越多应用于预测复杂性状；然而，非欧洲人群的次优表现引发了对临床应用和健康的担忧。
附：英文原文
Title: A new method for multiancestry polygenic prediction improves performance across diverse populations
Author: Zhang, Haoyu, Zhan, Jianan, Jin, Jin, Zhang, Jingning, Lu, Wenxuan, Zhao, Ruzhang, Ahearn, Thomas U., Yu, Zhi, OConnell, Jared, Jiang, Yunxuan, Chen, Tony, Okuhara, Dayne, Garcia-Closas, Montserrat, Lin, Xihong, Koelsch, Bertram L., Chatterjee, Nilanjan
Issue&Volume: 2023-09-25
Abstract: Polygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1million individuals of diverse ancestry, with 1.18million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction.
DOI: 10.1038/s41588-023-01501-z
Source: https://www.nature.com/articles/s41588-023-01501-z
Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex
本期文章：《自然—遗传学》：Online/在线发表
