Microbial, immune, metabolic perturbations by antibiotics (MIME study)

 描述（由申请方提供）：抗生素引起的微生物、免疫、代谢扰动（MIME研究）。仅在美国，每年就有超过2.5亿个疗程的抗生素在门诊护理中使用，其中包括4000多万名18岁以下的儿童。认为抗生素的使用具有最小的伴随不良副作用的观念导致了在临床情况下抗生素的过度使用，当它们没有严格指示时。因此，在医生和公众中，由于抗生素的使用似乎相对没有毒性，尽管感知或测量的益处很小，但似乎没有抑制其使用的因素。我们已经了解了很多关于人类微生物组的知识--生活在我们体内和体表的巨大的、高度多样化的细菌群落。新兴的观点是我们的微生物群和我们的细胞之间深刻的终身双向相互作用;本质上，我们的微生物群是人类生理学的核心部分。微生物群的扰动影响实验动物模型中的代谢、免疫和认知生理学。当一个人服用抗生素时，抗生素通过血液扩散到身体的各个部位，选择耐药性。我们建议研究两种常用抗生素[四环素（多西环素）和β-内酰胺（阿莫西林）]对人类微生物种群以及代谢和免疫生理学的影响，在NIH临床中心（CC）的随机临床试验中研究健康的人类志愿者。我们的假设是，除了严重干扰人体微生物组外，这些药物还将具有可测量的代谢和免疫效应，并在随后的几周内产生残留效应。为了验证这一假设，在目标1中，我们将评估抗生素的短暂治疗过程对微生物群和宏基因组组成的影响。在初步评估期后，将给予抗生素7天，并将进行长期的治疗后评估。将在总共10个时间点的每个时间点从多个研究中心获得标本，并用于估计细菌和真菌组成和基因含量。在目标2中，我们将评估抗生素疗程对免疫生理学的影响。在每个时间点，将采集血液、尿液和粪便，以测定先天性和适应性免疫标志物的血浆和细胞水平。在目标3中，我们将评估抗生素疗程对代谢生理学的影响。将评估获得的血液和尿液标本的代谢和激素生理学标志物。在一部分受试者中，我们将利用独特的CC代谢室来量化24小时能量消耗及其组成部分（睡眠、饮食诱导和活动）以及碳水化合物和脂肪利用率。除了主要数据分析外，我们还将建立一个整合时间数据的信息模型，以深入了解微生物组和宿主之间复杂交织的生理机能。该项目是一个机会，对每年给数千万人使用的药物进行全面和综合的评估。仔细分析和开发一个综合模型，以了解扰动的病理生理学，可能会发现雷达下的问题的指纹。

 DESCRIPTION (provided by applicant): Microbial, immune, metabolic perturbations by antibiotics (MIME study). More than 250 million courses of antibiotics are prescribed annually in the ambulatory care setting in the United States alone, including more than 40 million in children under 18 years of age. The perception that antibiotic use has minimal attendant adverse side effects contributes to the over-utilization of antibiotics in clinical circumstances when they are not strictly indicated. Thus, among physicians and the public alike, since the use of antibiotics seems to be relatively free of toxicity, there appears to be no disincentive to their use despite marginal perceived or measured benefit. We have learned much about the human microbiome -- the large, highly diverse, bacterial community that lives in and on us. The emerging view is of profound life-long bi- directional interactions between our microbiota and our cells; in essence, our microbiota are a central part of human physiology. Perturbations in the microbiota affect metabolic, immune, and cognitive physiology in experimental animal models. When a person takes an antibiotic, the antibiotic diffuses via the blood into all body compartments, selecting fo resistance. We propose to examine the effects of two commonly used antibiotics [a tetracycline (doxycycline) and a beta-lactam (amoxicillin)] on human microbial populations and on metabolic and immune physiology, studying healthy human volunteers in a randomized clinical trial at the NIH Clinical Center (CC). Our hypothesis is that in addition to acutely perturbing the human microbiome, these agents will have measurable metabolic and immunologic effects, with residual effects in the weeks that follow. To test this hypothesis, in Aim 1, we will assess the effects of a brief therapeutic course of antibiotics on microbiota and metagenome composition. After an initial evaluation period, antibiotics will be given for seven days, and there will be a prolonged post-treatment evaluation. Specimens will be obtained from multiple sites at each of 10 time-points in total, and used for estimating bacterial and fungal composition and gene content. In Aim 2, we will assess the effects of the antibiotic course on immune physiology. At each time point, blood, urine, and feces will be obtained to determine plasma and cellular levels of markers of both innate and adaptive immunity. In Aim 3, we will assess the effects of the antibiotic course on metabolic physiology. The obtained blood and urine specimens will be assessed for markers of metabolic and hormonal physiology. In a subset of subjects, we will utilize the unique CC Metabolic Chamber to quantify 24-hour energy expenditure and its components (sleeping, diet-induced, and activity) and carbohydrate and fat utilizations. In addition to the primary data analyses, we will build an informatic model integrating the temporal data to provide insight into the complex intertwined physiology between microbiome and host. This project is an opportunity to perform comprehensive and integrated evaluations of pharmacologic agents given to tens of millions of people every year. Careful analysis and development of an integrated model to understand the pathophysiology of the perturbations may identify the fingerprints of problems that had been below the radar.