Pitfalls of predicting age-related traits by polygenic risk scores

IF 1 4区 生物学 Q4 GENETICS & HEREDITY Annals of Human Genetics Pub Date : 2023-07-07 DOI:10.1111/ahg.12520
Valentina Escott-Price, Karl Michael Schmidt
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引用次数: 2

Abstract

Polygenic risk scores (PRS) are a method increasingly used to capture the combined effect of genome-wide significant variants and those which individually do not show genome-wide significant association but are likely to contribute to the risk of developing diseases. However, their practical use incurs complications and inconsistencies that so far limit their clinical applicability. The aims of the present review are to discuss the PRS for age-related diseases and to highlight pitfalls and limitations of PRS prediction accuracy due to ageing and mortality effects. We argue that the PRS is widely used but the individual's PRS values differ substantially depending on the number of genetic variants included, the discovery GWAS and the method employed to generate them. Moreover, for neurodegenerative disorders, although an individual's genetics do not change with age, the actual score depends on the age of the sample used in the discovery GWAS and is likely to reflect the individual's disease risk at this particular age. Improvement of PRS prediction accuracy for neurodegenerative disorders will come from two sides, both the precision of clinical diagnoses, and a careful attention to the age distribution in the underlying samples and validation of the prediction in longitudinal studies.

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通过多基因风险评分预测年龄相关特征的陷阱
多基因风险评分(PRS)是一种越来越多地用于捕捉全基因组显著变异和那些单独不显示全基因组显著关联但可能导致疾病风险的变异的综合影响的方法。然而,它们的实际使用会引起并发症和不一致性,到目前为止限制了它们的临床适用性。本综述的目的是讨论与年龄有关的疾病的PRS,并强调由于老龄化和死亡率的影响,PRS预测准确性的缺陷和局限性。我们认为,PRS被广泛使用,但个体的PRS值在很大程度上取决于所包含的遗传变异的数量、GWAS的发现和产生它们的方法。此外,对于神经退行性疾病,尽管个体的遗传学不随年龄变化,但实际得分取决于发现GWAS时所用样本的年龄,并可能反映个体在该特定年龄的疾病风险。神经退行性疾病PRS预测准确性的提高将来自两个方面,一是临床诊断的准确性,二是对基础样本年龄分布的仔细关注,以及在纵向研究中对预测的验证。
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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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