The impact of age on genetic risk for common diseases.
The impact of age on genetic risk for common diseases.
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DOI：
10.1371/journal.pgen.1009723
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发表时间：
2021-08
期刊：
影响因子：
4.5
通讯作者：
McVean G
中科院分区：
文献类型：
--
作者：
Jiang X;Holmes C;McVean G
遗传基因变异导致许多复杂疾病的个体风险，并越来越多地被用于预测患者分层。之前的研究已经表明，遗传因素与人类特征在不同年龄和其他背景下的相关性并不相同，尽管这种差异的原因尚不清楚。在这里，我们介绍了一些方法来推断疾病的遗传相对风险与年龄之间的纵向关系的形式，并检验是否所有的遗传风险因素的表现相似。我们在基于区间的审查方法中使用比例风险模型来估计年龄变化的个体变异对英国生物库英国祖先子集内24种常见疾病的遗传相对风险的贡献，应用贝叶斯聚类方法根据它们随年龄的相对风险分布来分组变异，并对年龄相关性和多样性进行排列测试。我们在九种疾病中发现了年龄变化相对风险曲线的证据，包括高血压、皮肤癌、动脉粥样硬化性心脏病、甲状腺功能减退症和胆结石，其中几种疾病显示出多个不同的遗传相对风险曲线的证据，尽管证据薄弱。主要模式显示，遗传风险因素对早期疾病风险的相对影响最大，随着时间的推移呈单调下降，至少对大多数变异来说是如此，尽管下降的幅度和形式因疾病而异。因此，对于遗传相对风险随着年龄增长而下降的疾病，与老年人群相比，遗传风险因素在年轻人群中具有更强的解释力。我们表明，这些模式不能用一个简单的模型来解释，该模型涉及环境因素等未观察到的协变量的存在。我们讨论了可能的模型，可以解释我们的观察结果以及对遗传风险预测的影响。我们从父母那里继承的基因影响着我们患几乎所有疾病的风险，从癌症到严重感染。随着基因组技术的爆炸性发展，我们现在能够利用个人的基因组来对未来的疾病风险做出有用的预测。然而，最近的研究表明，遗传信息的预测价值因环境而异，包括年龄、性别和种族。在本文中，我们引入、验证和应用新的统计学方法来研究年龄和遗传风险贡献之间的关系。这些方法允许我们提出一些问题，比如相对风险是否随着时间的推移是恒定的，相对风险是如何随着时间的推移而变化的，以及是否所有的遗传风险因素都有类似的年龄特征。通过将这些方法应用于英国生物库的数据，我们发现，随着年龄的增长，遗传相对风险有下降的趋势。该研究对50万人进行了前瞻性研究。我们考虑了对观察到的一系列可能的解释，并得出结论，肯定存在我们目前不知道的作用过程，例如在生命的不同阶段，遗传风险表现出来，或者基因和环境之间的相互作用。
Inherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Previous work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the longitudinal relationship between genetic relative risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic relative risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their relative risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying relative risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic relative risk. The predominant pattern shows genetic risk factors having the greatest relative impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants, although the magnitude and form of the decrease varies among diseases. As a consequence, for diseases where genetic relative risk decreases over age, genetic risk factors have stronger explanatory power among younger populations, compared to older ones. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction. The genes we inherit from our parents influence our risk for almost all diseases, from cancer to severe infections. With the explosion of genomic technologies, we are now able to use an individual’s genome to make useful predictions about future disease risk. However, recent work has shown that the predictive value of genetic information varies by context, including age, sex and ethnicity. In this paper we introduce, validate and apply new statistical methods for investigating the relationship between age and the contributions of genetic risk. These methods allow us to ask questions such as whether relative risk is constant over time, precisely how relative risk changes over time and whether all genetic risk factors have similar age profiles. By applying the methods to data from the UK Biobank, a prospective study of 500,000 people, we show that there is a tendency for genetic relative risk to decline with increasing age. We consider a series of possible explanations for the observation and conclude that there must be processes acting that we are currently unaware of, such as distinct phases of life in which genetic risk manifests itself, or interactions between genes and the environment.
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