Association of habitual sleep duration with plasma metabolomics

习惯性睡眠时间与血浆代谢组学的关联

• 批准号: 10004739
• 负责人: Kenneth P Wright
• 金额: $ 12.51万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10004739
• 关键词: Accidents; Address; Adult; Affect; American; Amino Acids; Anxiety; Automobile Driving; Biochemical; Biochemical Pathway; Biological; Biological Markers; Blood; Branched-Chain Amino Acids; Cardiovascular Diseases; Chronic; Chronic Disease; Coupled; Data; Data Set; Development; Diabetes Mellitus; Disease; Drug abuse; Educational workshop; Etiology; Exploratory/Developmental Grant for Diagnostic Cancer Imaging; Fatigue; Genomics; Glutamates; Goals; Health; Heart Diseases; Hematological Disease; Hour; Individual; Inflammation; Investigation; Laboratories; Laboratory Study; Life Style; Link; Longevity; Lung diseases; Measures; Mental Depression; Metabolic; Metabolic Diseases; Metabolic Marker; National Heart, Lung, and Blood Institute; Normal Range; Nurses; Nurses' Health Study; Obesity; Occupations; Outcome; Pathway interactions; Pattern; Plasma; Population; Primary Prevention; Prospective Studies; Proteomics; Public Health; Quality of life; Reporting; Research; Resolution; Resources; Risk; Risk Factors; Serotonin; Sleep; Sleep Deprivation; Sleep Disorders; Snoring; Sphingolipids; Stress; Technology; Time; Tryptophan; United States National Institutes of Health; Wakefulness; Weight Gain; Woman; Women' s Health; acylcarnitine; base; behavioral pharmacology; cardiometabolic risk; cardiometabolism; circadian; cohort; cost effective; disorder risk; epidemiology study; follow-up; high risk; insight; metabolic phenotype; metabolic profile; metabolomics; mortality; novel; obesity risk; potential biomarker; prospective; secondary analysis; shift work; sleep behavior; sleep health; sleep quality; small molecule; tool

An estimated 50 to 70 million Americans suffer from sleep and wakefulness disorders and approximately 45% of Americans sleep less or more than the recommended 7-9 hours per night. Both those short and long nightly sleep durations, outside of the 7-9 hours range, are associated with health problems including inflammation, depression and anxiety, diabetes, stress, drug abuse, poor quality of life, obesity, and fatigue related accidents on the job/while driving. However, mechanisms underlying such negative health consequences of short and long habitual sleep durations are poorly defined. Given technological advances in omics-based analyses over the past decade, metabolomics represents a viable approach to characterize thousands of small molecules in plasma thus facilitating detailed characterization of individual metabolic phenotypes. Supporting this, a key outcome of the 2015 NHLBI workshop entitled “Developing Biomarker Arrays Predicting Sleep and Circadian- Coupled Risks to Health” called for the use of omics approaches to identify markers of long-term sleep behavior. Thus, plasma metabolomics is an attractive approach to identify the impact of habitual short and long sleep durations on biochemical mechanisms linked to disease risk and negative health outcomes. The overall goal of this R21 award is to use existing sleep and plasma metabolomics data within established cohorts to identify metabolite markers of long-term sleep duration and their contribution to subsequent weight gain – an important chronic disease risk factor. Specifically, we will use existing metabolomics data from three well-characterized cohorts—Women’s Health Initiative, Nurses’ Health Study, and Nurses’ Health Study II—to identify altered plasma metabolites associated with habitual short and long sleep durations. We expect our findings will advance our understanding of how habitual sleep duration impacts mechanisms and biochemical pathways underlying weight-gain and cardiometabolic disease risk. Furthermore, metabolites altered by either short or long habitual sleep durations can serve as potential biomarkers of overall sleep health, setting the stage for follow-up analyses. Our aims are responsive to key goals of PAR-17-004 “Secondary Analyses of Existing Datasets in Heart, Lung, and Blood Diseases and Sleep Disorders”, and supports the 2011 NIH Sleep Disorders Research Plan to “Identify genomic, proteomic, metabolic, and developmental biomarkers of sleep deficiency and biological timing enabling objective assessments of the associated health risks.”

据估计，有5000万至7000万美国人患有睡眠和觉醒障碍，约45% 的美国人每晚睡眠时间少于或超过推荐的7-9小时。无论是晚上的短的还是长的 睡眠时间超过7-9小时与包括炎症在内的健康问题有关， 抑郁和焦虑、糖尿病、压力、滥用药物、生活质量差、肥胖和与疲劳相关的事故 在工作中[开车时]然而，短期和长期的这种负面健康后果背后的机制 习惯性睡眠的持续时间定义不明确。鉴于基于组学的分析中的技术进步 在过去的十年里，代谢组学代表了一种可行的方法来表征成千上万的小分子 因此，血浆有助于详细描述个体的代谢表型。支持这一点，一把钥匙 2015年NHLBI研讨会的成果，题为“开发预测睡眠和昼夜节律的生物标志物阵列-- 对健康的双重风险“呼吁使用组学方法来确定长期睡眠行为的标志。 因此，血浆代谢组学是确定习惯性短睡眠和长睡眠影响的一个有吸引力的方法。 与疾病风险和负面健康结果有关的生化机制的持续时间。的总目标是 这项R21奖是利用现有的睡眠和血浆代谢组学数据在已建立的队列中确定 长期睡眠时间的代谢物标志物及其对随后体重增加的贡献--一个重要的 慢性病危险因素。具体地说，我们将使用现有的代谢组学数据，这些数据来自三个特征良好的 队列-妇女健康倡议、护士健康研究和护士健康研究II-确定改变 与习惯性短睡眠和长睡眠有关的血浆代谢物。我们预计我们的发现将会取得进展 我们对习惯性睡眠时间如何影响机制和生化途径的理解 体重增加和心脏代谢性疾病风险。此外，由短的或长的习惯改变的代谢物 睡眠持续时间可以作为整体睡眠健康的潜在生物标记物，为后续分析奠定基础。 我们的目标是响应PAR-17-004的关键目标：对现有心肺数据集进行二次分析， 和血液疾病和睡眠障碍“，并支持2011年美国国立卫生研究院睡眠障碍研究计划 确定睡眠不足和生物计时的基因组、蛋白质组、代谢和发育生物标记物 从而能够对相关的健康风险进行客观评估。