Genome-wide association study of sleep spindles and related polysomnography measures

 描述（由申请人提供）：睡眠纺锤波是第2阶段非快速眼动睡眠（N2）的定义特征，在脑电图中明显表现为12- 15 Hz同步活动的短暂强大爆发。它们在丘脑网状核中产生，并通过丘脑皮质回路同步。Spectrometry是突触可塑性的一种机制，与记忆巩固和智商密切相关。精神分裂症在神经精神和神经发育疾病（包括精神分裂症、自闭症、重度抑郁症和智力残疾）患者以及精神分裂症患者的一级亲属中是异常的。这表明睡眠纺锤波是以认知障碍为特征的神经精神和神经发育障碍的潜在内表型。重要的是，睡眠纺锤波可以被人为操纵，增加纺锤波可以改善健康个体的记忆巩固，这表明纺锤波是一种新的治疗靶点。因此，确定纺锤体活动的遗传贡献将阐明 它们的机制，并可能指导治疗的发展。虽然纺锤体是高度遗传的，但对驱动其表达变异的特定基因知之甚少。为了解决这个问题，我们首先建议利用现有的大规模数据集来阐明 睡眠纺锤波的遗传结构以及其他可遗传的睡眠参数。其次，我们将研究已知的神经精神和神经发育障碍的遗传风险因素对纺锤波和其他睡眠参数的影响。我们将利用来自全基因组关联研究（GWAS）的单核苷酸多态性（SNP）数据，这些研究先前通过国家睡眠研究资源（NSRR）对大型睡眠研究队列进行，该资源包含脑电图（EEG）和数千人的遗传数据。大多数NSRR研究的目的是检查医学睡眠障碍，如阻塞性睡眠呼吸暂停，因此这些数据代表了一个宝贵的资源尚未挖掘的认知和神经精神遗传研究。具体来说，我们将开发一个计算管道来处理数千个整夜的EEG记录，检测纺锤波并报告睡眠结构的其他方面，包括频谱功率。我们将对这些表型进行全基因组关联研究，并使用最先进的分析方法来表征这些睡眠参数的遗传结构，重点关注共享遗传性以及精神疾病风险基因在多大程度上也涉及睡眠期间大脑活动的个体差异。通过使用遗传范式，这项研究可以解决睡眠，认知和疾病之间的机制和因果关系。

 DESCRIPTION (provided by applicant): Sleep spindles are a defining characteristic of Stage 2 non-rapid eye movement sleep (N2), evident in the electroencephalogram as brief powerful bursts of 12-15Hz synchronous activity. They are generated in the thalamic reticular nucleus and are synchronized by thalamocortical circuitry. Spindles are a mechanism of synaptic plasticity and are strongly linked to memory consolidation and IQ. Spindles are abnormal in patients with neuropsychiatric and neurodevelopmental illnesses (including schizophrenia, autism, major depression and intellectual disability) as well as in the first-degree relatives of individuals with schizophrenia. This suggests that sleep spindles are a potential endophenotype for neuropsychiatric and neurodevelopmental disorders characterized by cognitive impairments. Importantly, sleep spindles can be pharmacologically manipulated, and increasing spindles improves memory consolidation in healthy individuals, suggesting that spindles are a novel therapeutic target. Identifying genetic contributions to spindle activity will therefore illuminate their mechanisms and potentially guide the development of treatments. Although spindles are highly heritable, very little is known about the specific genes that drive variation in their expression. To address this, we first propose to exploit existing large-scale datasets to elucidate the genetic architecture of sleep spindles as well as other heritable sleep parameters. Second, we will examine the effects of known genetic risk factors for neuropsychiatric and neurodevelopmental disorders on spindle and other sleep parameters. We will leverage single nucleotide polymorphism (SNP) data from genome-wide association studies (GWAS) previously performed on large sleep study cohorts, via the National Sleep Research Resource (NSRR), which contains electroencephalography (EEG), and genetic data on thousands of individuals. Most NSRR studies were designed to examine medical sleep disorders such as obstructive sleep apnea and so these data represent a valuable resource not yet mined for cognitive and neuropsychiatric genetic research. Specifically, we will develop a computational pipeline to process the thousands of whole-night EEG recordings, detect spindles and report on other aspects of sleep architecture, including spectral power. We will perform a genome-wide association study for these phenotypes and use state-of-the-art analysis methods to characterize the genetic architecture of these sleep parameters, with a focus on shared heritability and the extent to which risk genes for psychiatric diseases are also implicated in individual differences in brain activity during sleep. By using a genetic paradigm, this research can address the mechanistic and causal relations between sleep, cognition and disease.