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本文引用的文献

1
Trans-biobank analysis with 676,000 individuals elucidates the association of polygenic risk scores of complex traits with human lifespan.对 67.6 万人进行的跨生物库分析阐明了复杂性状的多基因风险评分与人类寿命之间的关联。
Nat Med. 2020 Apr;26(4):542-548. doi: 10.1038/s41591-020-0785-8. Epub 2020 Mar 23.
2
Utility and First Clinical Application of Screening Embryos for Polygenic Disease Risk Reduction.用于降低多基因疾病风险的胚胎筛查的效用及首次临床应用
Front Endocrinol (Lausanne). 2019 Dec 4;10:845. doi: 10.3389/fendo.2019.00845. eCollection 2019.
3
Making the Most of Clumping and Thresholding for Polygenic Scores.充分利用聚类和阈值处理多基因评分。
Am J Hum Genet. 2019 Dec 5;105(6):1213-1221. doi: 10.1016/j.ajhg.2019.11.001. Epub 2019 Nov 21.
4
The genetics of human ageing.人类衰老的遗传学。
Nat Rev Genet. 2020 Feb;21(2):88-101. doi: 10.1038/s41576-019-0183-6. Epub 2019 Nov 5.
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A Prospective Analysis of Genetic Variants Associated with Human Lifespan.与人类寿命相关的遗传变异的前瞻性分析。
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Towards clinical utility of polygenic risk scores.迈向多基因风险评分的临床应用。
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7
Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood.从出生到成年的体重和肥胖轨迹的多基因预测。
Cell. 2019 Apr 18;177(3):587-596.e9. doi: 10.1016/j.cell.2019.03.028.
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UK Biobank, big data, and the consequences of non-representativeness.英国生物银行、大数据与代表性不足的后果。
Lancet. 2019 Mar 30;393(10178):1297. doi: 10.1016/S0140-6736(18)33067-8.
9
Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates.全基因组关联研究鉴定了自我报告的习惯性睡眠时长的遗传位点,这些时长是通过加速度计估计得出的。
Nat Commun. 2019 Mar 7;10(1):1100. doi: 10.1038/s41467-019-08917-4.
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Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.对多达 120 万人的关联研究为烟草和酒精使用的遗传病因学提供了新的见解。
Nat Genet. 2019 Feb;51(2):237-244. doi: 10.1038/s41588-018-0307-5. Epub 2019 Jan 14.

25 种疾病和风险因素多基因风险评分联合用于分层全因死亡率风险。

Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality.

机构信息

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Department of Statistics, University of Hong Kong, 999077, Hong Kong.

出版信息

Am J Hum Genet. 2020 Sep 3;107(3):418-431. doi: 10.1016/j.ajhg.2020.07.002. Epub 2020 Aug 5.

DOI:10.1016/j.ajhg.2020.07.002
PMID:32758451
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7477009/
Abstract

While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.

摘要

尽管全基因组关联研究已经确定了许多性状的易感变体,但它们在预测广泛的健康指标(如死亡率)方面的综合效用仍知之甚少。我们使用英国生物库的数据,将 13 种疾病和 12 种死亡风险因素的多基因风险评分 (PRS) 组合成性别特异性综合 PRS (cPRS)。这些 cPRS 与英国生物库内独立数据中的全因死亡率中度相关:女性和男性的估计风险比(每标准差)分别为 1.10(95%置信区间:1.05,1.16)和 1.15(1.10,1.19)。估计 cPRS 排名前 5%和后 5%的女性和男性之间的预期寿命差异分别为 4.79(1.76,7.81)年和 6.75(4.16,9.35)年。在调整研究入组时测量的非遗传死亡风险因素(即大多数参与者的中年)后,这些关联明显减弱。cPRS 可能有助于对遗传死亡风险较高的年轻个体进行非遗传因素改变的咨询。