Sleep and Cancer: Evaluation of Risk and Insights into Mechanisms

项目摘要/摘要 疾控中心最近宣布睡眠不足是一种“公共卫生流行病”，并指出估计有50-70人睡眠不足。 数百万美国成年人患有睡眠或觉醒障碍。尽管众所周知，睡眠不足 增加了许多慢性病的风险，但睡眠在癌症发展中的作用尚不清楚。而当 流行病学研究很少，它们得出了一些具有挑衅性但不一致的结论。是这样的 不一致可能反映了潜在病因机制的复杂性。睡眠起着根本性的作用 在维持致癌不可或缺的一些关键过程中，包括炎症和 细胞复制和增殖。此外，可能存在个体差异的脆弱性 睡眠不足的影响，取决于时型(即一个人的内源性生物节律是否 睡眠/清醒遵循早晨或晚上的偏好)。我们的目标是增进对 睡眠不足如何影响癌症风险，同时考虑潜在的潜在机制和宿主 脆弱性。这项研究将利用#年加州教师研究(CTS)提供的资源 这65,000名女性提供了关于睡眠和时型的详细自我报告数据，其中一部分 还提供了可用于进行生物标记物分析的血液样本，以量化生理影响。 具体目标是：1.评估与CTS患者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生物标志物的关系 对慢性炎症和端粒长度的影响；评估癌症风险和 睡眠不足的生理反应因时型而异。在实现这些目标的过程中，有几个具体的目标 将考虑睡眠不足的各个方面，包括睡眠质量差，睡眠持续时间过长， 睡眠零散，睡眠潜伏期长。侵袭性乳腺及其他常见诊断病例 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)将通过连锁进行识别 加州癌症登记处。生物标志物分析将对800份来自非政府组织的血液样本进行检测 癌症病例一年内的睡眠和时型数据。将使用多重免疫测定分析来 量化炎症循环生物标志物的水平。定量聚合酶链式反应将被用于测量端粒 长度。将使用COX比例风险模型和普通Logistic回归模型来估计 睡眠不足的每个维度，并根据其他已知的风险因素进行调整。多变量线性模型将是 用来描述生物标志物和睡眠的特定维度之间的关系。初始模型 将扩大，纳入时型，以探索时型在风险和/或影响方面的潜在差异。 该项目的长期目标支持NCI的使命，即通过进一步促进 我们对其病因和预防途径的理解。此外，它还支持NIH最近确定的 优先促进对睡眠和昼夜节律功能在健康和疾病中的理解。

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.