Red and Processed Meat Effects on the Metabolome and Microbiome

项目摘要 最近的争论是关于经常摄入红肉和加工肉类是否是 健康的饮食，或是否应避免或只适量食用红肉和加工肉类。 消费者和医疗保健专业人员对这些相反的观点感到困惑，需要进行研究， 明确指导饮食建议。观察性队列研究发现，那些自我报告 经常摄入红肉和加工肉类会增加患上与饮食有关的慢性疾病的风险， 心血管疾病，II型糖尿病和癌症相比，那些低或没有摄入这些食物。 这些发现是有价值的，但自我报告的饮食没有生物标志物并不能推进科学 对理解生物学机制的影响一些队列研究报告了红色和 加工肉类消费和健康相关的生物标志物，如脂质或食物分解产生的 生物标志物，如多环芳烃（PAH）和杂环胺（HA）。但不少 这些研究中的一项检查了红肉和加工肉与血液或尿液生物标志物的关系， 部分分析，留下的可能性，剩余的混淆和无法得出因果关系的推论。 此外，在这些研究中通常仅测量一种途径或一种化合物，限制了对多种途径或化合物的了解。 受红肉和加工肉类消费影响的途径。没有研究测试过红色和处理过的 使用代谢组和微生物组对全系统生物标志物进行肉类检测。为了克服这些证据缺口 我们将进行一项严格的随机交叉喂养试验，这是一项最适合于 研究由于能够仔细控制食物而将食物摄入与代谢反应联系起来的机制 摄入该试验性控制喂养试验将招募20名健康的成年女性和男性。参与者将 消费两种饮食，以随机顺序：1）饮食A是基于健康饮食指数-2015（HEI-2015）， 不包括红肉或加工肉类; 2）饮食B基于健康饮食指数-2015，包括红肉和 加工肉类（HEI-2015-M）作为主要蛋白质来源。两个饮食期都持续21天， 在饮食之间出现洗脱期。所有的食物都是在代谢厨房里准备的， 参与者或由快递员送到家中。两种类型的机械生物标志物是这种结果 这两项研究都反映了全系统的读数：（1）代谢组学;（2）肠道微生物群。血液，24小时尿液 在试验饲料前后收集粪便，以测试这些特定的目的：（1）识别程度 与HEI-2015-M相比，当食用标准HEI-2015饮食时代谢组的变化和性质 饮食;和（2）识别和表征当食用标准品时肠道微生物群落的调节 HEI-2015饮食与HEI-2015-M饮食的比较。这项试点试验预计将提供发现， 关于红肉和加工肉摄入量对人体代谢影响的数据，将用于设计和 一个更大的随机对照试验。

PROJECT SUMMARY Recent controversy has arisen concerning whether frequent intake of red and processed meat can be part of a healthy diet, or whether red and processed meat should be avoided or consumed only in moderation. Consumers and health care professionals are confused by these opposing views and research is needed to definitively guide dietary recommendations. Observational cohorts have found that those who self-report frequent red and processed meat intake have higher risk of several diet-related chronic diseases such as cardiovascular disease, type II diabetes and cancer compared to those with low or no intake of these foods. These findings are valuable, but self-reported diet without biological markers does not advance science towards understanding biological mechanisms. Some cohort studies have reported links between red and processed meat consumption and health related biomarkers such as lipids or food preparation-generated biomarkers such as polycyclic aromatic hydrocarbons (PAHs) and heterocyclic amines (HAs). However, many of these studies examined the associations of red and processed meat with blood or urine biomarkers in cross- sectional analyses, leaving the possibility for residual confounding and an inability to draw causal inference. Further, often only one pathway or one compound was measured in these studies, limiting insight into multiple pathways affected by red and processed meat consumption. And no studies have tested red and processed meat on systems-wide biomarkers using the metabolome and microbiome. To overcome these evidence gaps we will conduct a rigorous randomized cross-over feeding trial, which is a study design optimally suited for investigating mechanisms linking food intake with metabolic response due to the ability to carefully control food intake. This pilot, controlled feeding trial will enroll 20 heathy adult females and males. Participants will consume two diets, in random order: 1) Diet A is based on the Healthy Eating Index-2015 (HEI-2015) and includes no red or processed meat; 2) Diet B is based on the Healthy Eating Index-2015 and includes red and processed meat (HEI-2015-M) as primary protein sources. Both diet periods last 21 days and a 21-day washout period occurs between diets. All food is prepared in a metabolic kitchen and either picked up by participants or delivered by courier to their homes. Two types of mechanistic biomarkers are outcomes for this study, both reflecting systems-wide readouts: (1) metabolomics; and (2) gut microbiota. Blood, 24-hour urine and stool are collected before and after the experimental diets to test these specific aims: (1) Identify the extent and nature of shifts in the metabolome when consuming a standard HEI-2015 diet compared to a HEI-2015-M diet; and (2) Identify and characterize modulation of the gut microbial community when consuming a standard HEI-2015 diet compared to a HEI-2015-M diet. This pilot trial is expected to provide discovery, mechanistic data on the impact of red and processed meat intake on human metabolism that will be used to design and power a larger randomized controlled trial.