美国伊坎医学院Paul F. O’Reilly和Clive J. Hoggart共同合作，近期取得重要工作进展。他们研究开发了BridgePRS方法，该方法可以利用跨祖先的共享遗传效应来增加多基因风险评分的可移植性。相关研究成果2023年12月20日在线发表于《自然—遗传学》杂志上。

研究人员创建了BridgePRS，这是一种新的贝叶斯多基因风险评分（PRS）方法，它利用祖先之间的共享遗传效应来提高PRS的可移植性。研究人员通过模拟和真实的英国生物库数据（UK Biobank）评估BridgePRS，这些数据涉及非洲、南亚和东亚血统个体的19个性状，使用英国生物库和日本生物库全基因组关联研究汇总统计数据，队列外验证在西奈山（纽约）BioMe生物库中进行。BridgePRS与领先的替代方案PRS CSx和其他两种PRS方法进行了比较。

模拟表明，BridgePRS相对于PRS-CSx的性能随着不确定性的增加而增加：性状遗传力较低，多原性较高，群体间遗传多样性较大；以及当数据中不存在因果变异时。在实际数据中，BridgePRS在BioMe中对非洲血统样本的队列外预测中的平均R²比PRS CSx高61%（P = 6×10⁻⁵）。BridgePRS是一种计算高效、用户友好且功能强大的方法，用于非欧洲祖先的PRS分析。

附：英文原文

Title: BridgePRS leverages shared genetic effects across ancestries to increase polygenic risk score portability

Author: Hoggart, Clive J., Choi, Shing Wan, Garca-Gonzlez, Judit, Souaiaia, Tade, Preuss, Michael, OReilly, Paul F.

Issue&Volume: 2023-12-20

Abstract: Here we present BridgePRS, a novel Bayesian polygenic risk score (PRS) method that leverages shared genetic effects across ancestries to increase PRS portability. We evaluate BridgePRS via simulations and real UK Biobank data across 19 traits in individuals of African, South Asian and East Asian ancestry, using both UK Biobank and Biobank Japan genome-wide association study summary statistics; out-of-cohort validation is performed in the Mount Sinai (New York) BioMe biobank. BridgePRS is compared with the leading alternative, PRS-CSx, and two other PRS methods. Simulations suggest that the performance of BridgePRS relative to PRS-CSx increases as uncertainty increases: with lower trait heritability, higher polygenicity and greater between-population genetic diversity; and when causal variants are not present in the data. In real data, BridgePRS has a 61% larger average R2 than PRS-CSx in out-of-cohort prediction of African ancestry samples in BioMe (P=6×105). BridgePRS is a computationally efficient, user-friendly and powerful approach for PRS analyses in non-European ancestries.

DOI: 10.1038/s41588-023-01583-9

Source: https://www.nature.com/articles/s41588-023-01583-9