Suppr超能文献

解决人类遗传研究中多基因评分面临的挑战。

Addressing the challenges of polygenic scores in human genetic research.

机构信息

Professional Practice and Social Implications Committee Polygenic Scores Guidance Writing Group, American Society of Human Genetics, Rockville MD, USA; Department of Human Genetics, University of Chicago, Chicago, IL, USA; Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.

Professional Practice and Social Implications Committee Polygenic Scores Guidance Writing Group, American Society of Human Genetics, Rockville MD, USA; Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.

出版信息

Am J Hum Genet. 2022 Dec 1;109(12):2095-2100. doi: 10.1016/j.ajhg.2022.10.012.

Abstract

The genotyping of millions of human samples has made it possible to evaluate variants across the human genome for their possible association with risks for numerous diseases and other traits by using genome-wide association studies (GWASs). The associations between phenotype and genotype found in GWASs make possible the construction of polygenic scores (PGSs), which aim to predict a trait or disease outcome in an individual on the basis of their genotype (in the disease case, the term polygenic risk score [PRS] is often used). PGSs have shown promise for studying the biology of complex traits and as a tool for evaluating individual disease risks in clinical settings. Although the quantity and quality of data to compute PGSs are increasing, challenges remain in the technical aspects of developing PGSs and in the ethical and social issues that might arise from their use. This ASHG Guidance emphasizes three major themes for researchers working with or interested in the application of PGSs in their own research: (1) developing diverse research cohorts; (2) fostering robustness in the development, application, and interpretation of PGSs; and (3) improving the communication of PGS results and their implications to broad audiences.

摘要

对数百万人的基因分型使得通过全基因组关联研究(GWAS)评估人类基因组中变体与多种疾病和其他特征的风险之间的可能关联成为可能。GWAS 中发现的表型与基因型之间的关联使得多基因评分(PGS)的构建成为可能,PGS 旨在根据个体的基因型(在疾病情况下,常使用多基因风险评分 [PRS] 一词)预测个体的特征或疾病结果。PGS 已显示出在研究复杂特征的生物学和作为临床环境中评估个体疾病风险的工具方面的潜力。尽管用于计算 PGS 的数据数量和质量在增加,但在开发 PGS 的技术方面以及在使用 PGS 可能引起的伦理和社会问题方面仍存在挑战。本 ASHG 指南强调了与在自己的研究中应用 PGS 相关或有兴趣的研究人员的三个主要主题:(1)开发多样化的研究队列;(2)在 PGS 的开发、应用和解释中促进稳健性;(3)提高 PGS 结果及其对广泛受众的影响的沟通。

相似文献

引用本文的文献

9
Genomic landscape of cancer in racially and ethnically diverse populations.不同种族和族裔人群中癌症的基因组格局。
Nat Rev Genet. 2025 May;26(5):336-349. doi: 10.1038/s41576-024-00796-w. Epub 2024 Nov 28.

本文引用的文献

5
Improving polygenic prediction in ancestrally diverse populations.提高在祖源多样化人群中的多基因预测能力。
Nat Genet. 2022 May;54(5):573-580. doi: 10.1038/s41588-022-01054-7. Epub 2022 May 5.
6
Population differentiation of polygenic score predictions under stabilizing selection.稳定选择下多基因评分预测的群体分化。
Philos Trans R Soc Lond B Biol Sci. 2022 Jun 6;377(1852):20200416. doi: 10.1098/rstb.2020.0416. Epub 2022 Apr 18.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验