Lipidomics Biomarkers Link Sleep Restriction to Adiposity Phenotype, Diabetes, and Cardiovascular Risk

长期的睡眠限制和睡眠模式的改变已经成为一种常见和严重的健康问题 和安全问题，而且越来越多的证据表明，睡眠中断直接导致和/或导致 代谢异常和疾病，包括糖尿病。然而，尽管有明显的需求，仍有AS 然而，没有客观的手段来评估慢性睡眠状态，对中间体的了解也有限 表型，特别是在不同的人群中。毫不奇怪，2011年美国国立卫生研究院睡眠障碍调查的第一个目标 研究计划是确定：“……新陈代谢……睡眠不足的生物标记物……这将有助于个性化 治疗，并澄清与未经治疗的睡眠以及昼夜节律紊乱和干扰有关的风险。 生物学上看似合理的是，限制/改变睡眠的代谢后果至少在某种程度上是 反映在个体循环中的血脂和总体肥胖状况的变化--即临床特征 与代谢综合征和显性糖尿病相关的、先于和预测的。相反，健康， 经常运动的成年人表现出脂肪分布，内脏和肝脏肥胖症水平相对较低。 不管他们的总体肥胖度如何。肥胖程度和类型的异质性存在于这五个群体中 多种族队列中的种族群体(MEC)提供了一个独特的研究环境，以更好地了解疾病 睡眠时间和睡眠模式异常的影响，这些变化如何与糖尿病风险相关，以及如何 这种关系会因年龄和种族而改变。更具体地说，我们提出了一个一般的观点--以及一组 假设：(I)睡眠受限和/或睡眠模式改变直接导致循环改变 短期和改变的肥胖表型的血脂(例如，内脏、肝脏和 (Ii)睡眠不足或睡眠模式改变的核心风险是种族和性别- 独立，但其对糖尿病风险的外显性受到不同种族内潜在风险的影响 (3)睡眠问题的后果持续存在，并增加糖尿病患者的死亡风险 具体地说，更广泛地说，在MEC。这项建议利用了约1850名老年人的数据 (年龄~65-70岁)DEXA/MRI-评估身体脂肪/分布(例如，内脏脂肪、肝脏脂肪、皮下脂肪等) 以及2400个嵌套(在MEC)、不同种族和不同年龄(年龄在50岁至80岁)的病例对照对的可用性 未来的糖尿病，以及布里格姆妇女医院现有的临床和睡眠研究数据。 识别睡眠不足或异常的生物标志物面板将影响科学和 健康：(1)促进临床对睡眠问题的认识和治疗(例如，咨询、药物)； (2)创建流行病学工具，将睡眠不足与疾病风险联系起来，并帮助其他疾病的发展 生物标志物；以及；(3)有助于研究睡眠生物学及其对人类健康的影响。完成 将进一步推动NIH的目标，即专注于健康和早期干预，而不是晚期疾病。这项研究是 完全在我们实验室的能力范围内，在4年内完成。

Chronic sleep restriction and altered sleep patterns have emerged as a common and serious health and safety issue, and there is growing evidence that disrupted sleep directly underlies and/or contributes to metabolic abnormalities and diseases, including diabetes. Despite the obvious need, however, there are as yet no objective means of assessing chronic sleep status and limited understanding of intermediate phenotypes, especially in diverse populations. Not surprisingly, the first goal of the 2011 NIH Sleep Disorders Research Plan is to identify: "...metabolic... biomarkers of sleep deficiency ... that will facilitate personalized treatments, and clarify the risk associated with untreated sleep and circadian disorders and disturbances." It is biologically plausible that the metabolic consequences of restricted/altered sleep are, at least at some level, reflected in shifts within an individual's circulating lipids and overall adiposity status -- i.e., the clinical hallmarks that associate with, precede, and predict, metabolic syndrome and overt diabetes. Conversely, healthy, physically active adults display a fat distribution with a relatively low level of visceral and liver adiposity – regardless of their overall adiposity. The heterogeneity in level and types of obesity that exists among the five ethnic groups in the Multiethnic Cohort (MEC) offers a unique research setting to better understand the ill effects of abnormalities in sleep duration and patterns, how these changes relate to diabetes risk, and how this relationship is modified by age and ethnicity. More specifically, we propose a general viewpoint -- and set of hypotheses, in which: (i) Sleep restriction and/or altered sleep patterns directly induce altered circulating lipids short-term and altered adiposity phenotypes (e.g., shifts in the ratios between visceral, liver, and subcutaneous fat) long-term; (ii) the core risk of insufficient sleep or altered sleep patterns is ethnic and sex- independent, but its penetrance on diabetes risk is influenced by the underlying risk within the different ethnic groups; (iii) the consequences of sleep problems continue and increase risk of mortality in diabetics specifically and, more generally, in the MEC. This proposal leverages data on ~1850 older individuals (age~65-70) DEXA/MRI-assessed for body fat/distribution (e.g., visceral fat, liver fat, subcutaneous fat, etc) and the availability of 2400 nested (in MEC), ethnically- and age-diverse (age~50 to 80) case-control pairs for future diabetes, as well as existing clinical and sleep study data in Brigham and Women's Hospital. Identification of biomarker panels for insufficient or abnormal sleep will impact multiple aspects of science and health: (i) contribute to clinical recognition and treatment (e.g., counseling, pharmaceuticals) of sleep issues; (ii) create epidemiologic tools to relate limited sleep with disease risk and aid development of other disease biomarkers, and; (iii) contribute to research on sleep biology and its implications for human health. Completion will further NIH goals of focusing on health and early interventions rather than late stage disease. The study is well within our lab's capacity to complete in 4 years.