Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits.
Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits.
复制标题
利用睡眠遗传发现来确定与常见复杂特征的因果关系。
DOI：
10.1093/sleep/zsac180
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发表时间：
2022
期刊：
影响因子：
5.6
通讯作者：
Grant,StruanFA
中科院分区：
文献类型：
--
作者：
Sonti,Shilpa;Grant,StruanFA
睡眠是普遍存在的，是人类功能的生物学必需品。睡眠质量下降的后果会影响身体和生理系统，例如神经、心血管和代谢过程。事实上，受常见复杂疾病影响的人们会经历各种各样的睡眠障碍。由于缺乏合适的睡眠生物标志物，揭示许多疾病系统中导致睡眠质量下降的潜在分子机制具有挑战性。然而，睡眠模式遗传成分的发现为检查和理解睡眠与许多疾病状态的关系提供了新的机会。现在可以利用主要的基因组资源和技术来揭示许多常见疾病的遗传因素。全基因组关联研究 (GWAS) 等大规模前瞻性研究已成功揭示了许多与睡眠相关特征相关的强大遗传信号。随着这些遗传变异的发现，社区的一个主要目标是研究睡眠相关特征是否与疾病发病机制和其他健康并发症相关。孟德尔随机化 (MR) 是一种利用遗传位点作为代理指标来确定睡眠特征与疾病结果之间因果关系的分析方法。鉴于此类变异在出生时随机遗传，MR 分析消除了混杂偏差，从而证明了可用于药物开发和临床试验优先顺序的因果关系证据。在这篇综述中，我们概述了迄今为止对与多种常见复杂疾病相关的睡眠特征进行的 MR 分析的结果。
Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.