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

代谢组学研究是一项相对较新的技术，用于鉴定由身体过程产生并参与调节代谢途径的代谢物。某些代谢物极有可能在疾病或药物治疗期间发生改变，因此，能够测量和识别这些（生物标志物）对于未来的健康和疾病诊断至关重要。然而，对于代谢组学分析在疾病诊断中对临床医生有价值而言，从健康对照中建立准确的基线数据至关重要。代谢组学数据的正确解释将需要对一天中的时间的影响以及一个人的内部生物（昼夜节律）计时系统对代谢组学特征的影响有透彻的了解。生物昼夜节律和一天中的时间变化发生在大多数生理标志物中，例如褪黑激素、皮质醇、葡萄糖;在血浆和尿液中鉴定的代谢物也不例外。然而，迄今为止，还没有使用已建立的昼夜节律方案对人体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/觉醒周期，膳食）如何影响代谢组学特征。因此，我们在健康志愿者中使用严格控制的实验室研究和尖端的代谢组学技术，旨在研究生物钟、一天中的时间、光/暗环境、饮食和睡眠对血浆和尿液中确定的节律性和非节律性代谢物的影响。代谢物，显示节律昼夜和时间的变化（循环）和那些不（非循环代谢物），以及受睡眠和睡眠剥夺影响的代谢过程，将通过使用尖端，高灵敏度，液相色谱-质谱（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），我们在与拟议研究相似的受控条件下获得了健康志愿者的初步数据。基于潜结构正交投影（OPLS）分析（Simca Software，沃茨），在至少20种血浆和20种尿液代谢物中观察到显著的日间变化。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。确定代谢节律以及这些节律如何受到外部因素（一天中的时间，觉醒，睡眠，环境照明，规律饮食）的影响将提供可靠的基线数据，这对于未来使用和正确解释代谢组学在人类疾病的检测和治疗中至关重要。此外，我们的项目合作伙伴（Erasmus MC大学医学中心（EUMC），鹿特丹）将在两项研究的24小时内对选定的样本进行蛋白质组和转录组分析，以合并数据。生物样本、代谢组学数据库和研究结果将被分享和传播，以造福于广泛参与疾病诊断和治疗的专业人员（例如临床医生、临床生物化学家），最终造福社会。

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.