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Using the Coriell Personalized Medicine Collaborative Data to conduct a genome‐wide association study of sleep duration

机译：使用Coriell个性化医学合作数据进行全基因组睡眠时间关联研究

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Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome‐wide association studies (GWAS). However, genome‐wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self‐reported sleep duration, demographic and lifestyle variables, and genome‐wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self‐reported data collected through the CPMC are robust, and our genome‐wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
机译：睡眠对健康和功能至关重要，许多研究使用全基因组关联研究（GWAS）研究了失眠和其他睡眠障碍的遗传成分。但是，针对睡眠时间的全基因组研究较少见。在这里，我们使用了来自Coriell个性化医学协作（CPMC）（n = 4401）参与者的数据，检查了自我报告的睡眠时间，人口统计学和生活方式变量与全基因组单核苷酸多态性（SNP）数据之间的推定关联。了解导致睡眠时间变化的遗传因素。我们采用逐步有序Logistic回归选择模型，并保留以下预测变量：年龄，性别，体重，体育锻炼，工作中的体育锻炼，吸烟状况，饮酒，种族和血统（通过主成分分析衡量）我们的协会测试。我们先前在GWAS中鉴定了几个最强的候选基因，这些基因与睡眠时间（TSHZ2，ABCC9，FBXO15）和嗜睡症（NFATC2，SALL4）有关。此外，我们已经确定了参与睡眠时间的新候选基因，包括SORCS1和ELOVL2。我们的结果表明，通过CPMC收集的自我报告数据是可靠的，并且我们的全基因组关联分析已确定了与睡眠时间有关的新候选基因。更广泛地说，这项研究有助于更好地了解人类睡眠的复杂性。 ©2015作者。 《美国医学遗传学杂志》 B部分：Wiley Periodicals，Inc.发布的神经精神遗传学。

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