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

机译:组合型疾病和风险因素的多种基因危险分数用于分层所有导致死亡率的风险

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摘要

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.
机译:虽然基因组关联研究已经确定了许多特征的易感性变异,但它们用于预测广泛的健康措施的合并效用,例如死亡率,仍然很糟糕。我们使用英国BioBank的数据将13种疾病和12个死亡率因素组合成性别特定的复合PRS(CPRS)。这些CPRS与英国BIOBANK内的独立数据中的所有原因死亡率适度相关:每个标准偏差的估计危险比分别为妇女和男性的估计危险比为1.10(95%置信区间:1.05,1.16)和1.15(1.10,1.19) 。估计CPR的顶部和底部5%之间的预期差异估计为4.79(1.76,7.81)岁,女性和男性分别为6.75(4.16,9.35)年。在调整在研究条目(即,中年大多数参与者的中年)测量后,这些关联在调整非遗传死亡率风险因素之后基本衰减。 CPRS可用于咨询年轻个体,以对非遗传因素的修改进行较高的遗传风险。

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