Sleep and Cancer: Evaluation of Risk and Insights into Mechanisms

项目总结/摘要 疾病预防控制中心最近宣布睡眠不足是一种“公共卫生流行病”， 在美国，有100万成年人患有睡眠或觉醒障碍。虽然众所周知，睡眠不足 增加了许多慢性疾病的风险，睡眠在癌症发展中的作用尚不清楚。而 虽然流行病学研究很少，但它们已经产生了一些挑衅性但不一致的发现。等 不一致性可能反映了潜在病因机制的复杂性。睡眠扮演着重要的角色 在维持一些关键过程中不可或缺的致癌作用，包括炎症和 细胞复制和增殖。此外，可能存在个体差异， 睡眠不足的影响，取决于时间类型（即，一个人的内源性生物节律 睡眠/觉醒遵循早晨或晚上偏好）。我们的目标是增进对 睡眠不足如何影响癌症风险，考虑潜在的潜在机制和宿主 易损性.这项研究将利用加州教师研究（CTS）提供的资源， 其中65，000名女性提供了关于睡眠和时钟类型的详细自我报告数据，其中一部分人 还提供了可用于进行生物标志物测定以量化生理效应的血液样品。 具体目标是：（1）评估CTS中与自我报告的睡眠不足相关的癌症风险 参与者; 2.评估自我报告的睡眠不足与生理指标之间的关系 对慢性炎症和端粒长度的影响; 3.）评估癌症风险的程度， 对睡眠不足的生理反应因时间类型而异。在实现每一个目标时， 睡眠不足的维度将被考虑，包括睡眠质量差，睡眠时间极端， 分段睡眠和长睡眠潜伏期。浸润性乳腺等常见病例 癌症（结直肠癌、黑色素瘤、子宫内膜癌、非霍奇金淋巴瘤、甲状腺癌）将通过关联进行识别 加州癌症登记处生物标志物检测将在800份血液样本上进行，这些血液样本来自非 一年内的癌症病例的睡眠和生理时钟数据。将使用多重免疫测定法， 量化炎症的循环生物标志物的水平。将使用定量PCR测量端粒 长度将使用考克斯比例风险和普通Logistic回归模型估计以下风险： 每个维度的睡眠不足，调整其他已知的风险因素。多变量线性模型将 用于表征生物标志物与睡眠的特定维度之间的关系。初始模型 将扩展，纳入时间型，以探索时间型的风险和/或影响的潜在差异。 该项目的长期目标支持NCI的使命，即通过进一步减少癌症负担， 我们对其病因和预防途径的了解。此外，它支持NIH最近确定的 优先促进对健康和疾病中睡眠和昼夜节律功能的理解。

Project Summary/Abstract The CDC recently declared insufficient sleep to be a “public health epidemic,” noting that an estimated 50-70 million US adults have sleep or wakefulness disorders. Although it is well-recognized that insufficient sleep increases the risk for many chronic conditions, the role of sleep in the development of cancer is unclear. While epidemiologic studies are sparse, they have yielded some provocative but inconsistent findings. Such inconsistencies may reflect the complexity of underlying etiologic mechanisms. Sleep plays a fundamental role in the maintenance of a number of key processes integral to carcinogenesis, including inflammation and cellular replication and proliferation. Furthermore, there may be individual differences in vulnerability to the effects of sleep deficiency, depending on chronotype (i.e., whether one’s endogenous biological rhythm of sleep/wakefulness follows a morning or evening preference). Our objective is to advance the understanding of how sleep deficiency may influence cancer risk, considering both potential underlying mechanisms and host vulnerability. The study will capitalize on resources available from the California Teachers Study (CTS) in which 65,000 women have provided detailed self-reported data on sleep and chronotype, a subset of whom have also provided blood samples available for the conduct of biomarker assays to quantify physiologic effects. The specific aims are to: 1.) evaluate cancer risks associated with self-reported sleep deficiency among CTS participants; 2.) assess the relationship between self-reported sleep deficiency and biomarkers of physiologic effect for chronic inflammation and telomere length; 3.) evaluate the degree to which cancer risks and the physiologic responses to sleep deficiency vary by chronotype. In addressing each of these aims, several specific dimensions of sleep deficiency will be considered, including poor sleep quality, extremes in sleep duration, fragmented sleep and long sleep latency. Cases of invasive breast and other selected commonly-diagnosed cancers (colorectal, melanoma, endometrial, non-Hodgkin’s lymphoma, thyroid) will be identified via linkage to the California Cancer Registry. Biomarker assays will be run on 800 blood samples collected from non- cancer cases within a year of the sleep and chronotype data. Multiplexed immunometric assays will be used to quantify levels of circulating biomarkers of inflammation. Quantitative PCR will be used to measure telomere length. Cox Proportional Hazards and Ordinary Logistic Regression models will be used to estimate risks for each dimension of sleep deficiency, adjusting for other known risk factors. Multivariable linear models will be used to characterize the relationship between the biomarkers and specific dimensions of sleep. Initial models will be expanded, incorporating chronotype to explore potential differences in risk and/or effect by chronotype. The long-term objective of this project supports the NCI’s mission to reduce the burden of cancer by furthering our understanding of its etiology and avenues for prevention. Additionally, it supports NIH’s recently identified priority to advance the understanding of sleep and circadian functions in health and disease.