Effect of the circadian clock time of day and sleep on the human metabolome: identification of metabolite rhythms

代谢组学的研究是一种相对较新的技术，用于识别由身体过程产生的、参与调节代谢途径的代谢物。某些代谢物在疾病或药物治疗期间极有可能发生变化，因此，能够测量和识别这些(生物标记物)将对未来的健康和疾病诊断至关重要。然而，要使代谢组谱在疾病诊断中对临床医生有价值，必须从健康对照中建立准确的基线数据。对代谢组数据的正确解释需要透彻地了解一天中时间的影响以及人体内部生物(昼夜)计时系统对代谢组谱的影响。大多数生理标记物如褪黑素、皮质醇、葡萄糖都存在生物昼夜节律和时间变化；在血浆和尿液中发现的代谢物也不例外。然而，到目前为止，还没有使用已建立的昼夜节律方案对人类代谢组中的昼夜节律变化进行系统研究。此外，需要确定典型的生活环境(光/暗周期、睡眠/清醒周期、饮食)如何影响代谢谱。因此，我们利用在健康志愿者中进行的严格控制的实验室研究和尖端的代谢组学技术，旨在表征生物钟、一天中的时间、明/暗环境、饮食和睡眠对血浆和尿液中识别出的节律性和非节律性代谢物的影响。显示节律昼夜节律和一天中时间变化(循环)的代谢物以及受睡眠和睡眠剥夺影响的代谢物(非循环代谢物)以及代谢过程将通过使用尖端、高灵敏的液质联用(LC-MS)技术进行鉴定。在萨里，我们在进行昼夜节律和睡眠剥夺实验方面拥有成熟的专业知识。使用我们最近建立的LC-MS方法(Surrey和ICR)，我们在健康志愿者中获得了类似于拟议研究的受控条件下的试点数据。根据对潜在结构的正交投影分析(Simca Software，Waters)，至少在20种血浆和20种尿代谢物中观察到了显著的一天时间变化。因此，就专业知识、临床和分析设施以及技术技能而言，该提案是可行的。确定代谢物节律以及这些节律如何受到外部因素(一天中的时间、清醒、睡眠、环境照明、规律饮食)的影响将提供可靠的基线数据，这些数据对于未来代谢组学在人类疾病检测和治疗中的使用和正确解释至关重要。此外，我们的项目合作伙伴(鹿特丹伊拉斯谟MC大学医学中心(EUMC))将对两项研究的选定样本进行24小时的蛋白质组和转录组分析，以期将数据结合起来。生物样本、代谢组数据库和研究结果将被共享和传播，以造福于参与疾病诊断和治疗的广泛专业人员(例如临床医生、临床生物化学家)，最终将造福社会。

The study of metabolomics is a relatively new technique to identify metabolites that are produced by body processes and are involved in regulatory metabolic pathways. It is highly likely that certain metabolites will be altered in disease or during drug therapy and thus, being able to measure and identify these (biomarkers) will be critical for future health and disease diagnostics. For metabolomic profiling to be of value for clinicians in the diagnosis of disease, however, it is essential to establish accurate baseline data from healthy controls. Correct interpretation of metabolomic data will require a thorough knowledge of the impact of time of day as well as the effect of a person's internal biological (circadian) timing system on the metabolomic profile. Biological circadian rhythms and time of day variation occur in most physiological markers e.g. melatonin, cortisol, glucose; metabolites identified in plasma and urine will be no exception. However, to date there has been no systematic study of circadian variation in the human metabolome using established circadian protocols. In addition how a typical living environment (light/dark cycle, sleep/wake cycle, meals) affects metabolomic profiles needs to be determined. Using strictly controlled laboratory studies in healthy volunteers and cutting edge metabolomic technology we thus aim to characterise the effect of the circadian clock, the time of day, the light/dark environment, meals and sleep on rhythmic and non-rhythmic metabolites identified in plasma and urine. Metabolites that show rhythmic circadian and time-of-day variation (cycling) and those that do not (non-cycling metabolites), as well as metabolic processes affected by sleep and sleep deprivation, will be identified through the use of cutting edge, highly sensitive, liquid chromatography-mass spectrometric (LC-MS) techniques. At Surrey we have proven expertise in conducting circadian and sleep deprivation experiments. Using our recently established LC-MS methodology (Surrey and ICR) we have pilot data in healthy volunteers kept in controlled conditions similar to the proposed studies. Significant time of day variation has been observed in at least 20 plasma and 20 urine metabolites, based on Orthogonal Projections to Latent Structures (OPLS) analysis (Simca Software, Waters). Therefore in terms of expertise, clinical and analytical facilities and technical skills the proposal is feasible. Identification of metabolite rhythms and how these are affected by external factors (time of day, wakefulness, sleep, environmental lighting, regular meals) will provide reliable baseline data which will be crucial for the future use, and correct interpretation, of metabolomics in the detection and treatment of human disease. In addition, our Project Partner (Erasmus MC University Medical Center (EUMC), Rotterdam) will perform proteome and transcriptome analysis on selected samples across the 24 h day from both studies with a view to combining the data. The biological samples, metabolomic database and research findings will be shared and disseminated for the benefit of a wide range of professionals involved in disease diagnosis and treatment (e.g. clinicians, clinical biochemists) which will ultimately benefit society.