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.”

估计有50至7000万美国人患有睡眠和清醒障碍，约45％ 美国人的睡眠少于建议每晚7-9个小时。那些短而漫长的夜间 睡眠持续时间（在7-9小时范围内）与健康问题有关，包括炎症， 抑郁和焦虑，糖尿病，压力，药物滥用，生活质量差，肥胖和疲劳相关事故 在工作/开车时。但是，短而长 习惯性睡眠时间的定义很差。鉴于基于OMIC的分析的技术进步 过去的十年，代谢组学代表了一种可行的方法，可以表征数千个小分子 血浆因此支持单个代谢表型的详细表征。支持这一点，一个钥匙 2015年NHLBI研讨会的结果名为“开发生物标志物阵列，预测睡眠和昼夜节律 对健康的耦合风险”要求使用OMICS方法来识别长期睡眠行为的标志。 那就是，血浆代谢组学是一种识别习惯短和长睡眠影响的有吸引力的方法 生化机制的持续时间与疾病风险和负面健康结果有关。总体目标 该R21奖是在已建立的同伙中使用现有的睡眠和血浆代谢组学数据来识别 长期睡眠持续时间的代谢物标记及其对随后体重增加的贡献 - 重要 慢性疾病危险因素。具体而言，我们将使用三个良好特征的现有代谢组学数据 队列 - 妇女的健康倡议，护士健康研究和护士健康研究II-以确定变化 血浆代谢产物与惯常的短睡眠时间有关。我们希望我们的发现会进步 我们对习惯性睡眠持续时间如何影响机制和生化途径的理解 体重增强和心脏代谢疾病风险。此外，代谢物被短或长习惯变化 睡眠时间可以作为整体睡眠健康的潜在生物标志物，为后续分析奠定了基础。 我们的目标是对PAR-17-004的关键目标的响应，“肺部现有数据集的次要分析， 以及血液疾病和睡眠障碍”，并支持2011年NIH睡眠障碍研究计划 “识别基因组，蛋白质组学，代谢和发展的生物标志物的睡眠不足和生物计时 实现对相关健康风险的客观评估。”