Serum Metabolomic/Proteomic Profiles in CALERIE

描述（由申请人提供）： 热量限制（CR）是已知的延长实验室啮齿动物寿命和降低发病率的最有效、最稳健和最可重复的方法。尽管经过70年的研究，这一观察结果对人类的相关性仍然未知。相关性得到了人类肥胖和发病率之间既定联系的支持。美国国立卫生研究院赞助的CALERIE（减少能量摄入的长期影响的综合评估）研究直接解决了潜在的联系。本研究将入组约250例受试者，并在24个月内的6个时间点采集血样。我们提出的辅助研究有两个目标：（A）通过表征这些样本中的血浆代谢组和蛋白质组来支持CALERIE;最初的焦点是确定是否预先存在的代谢组学图谱，以及NIH资助的研究中正在开发的蛋白质组学图谱，使我们能够跟踪来自三个不同地理位置的人的CR（从而将人类研究与啮齿动物文献联系起来），并确定感兴趣的代谢物和途径;（B）提供数据基础，并将PI正在进行的使用CR大鼠的代谢组学和蛋白质组学特征预测未来II型糖尿病和乳腺癌疾病风险的研究联系起来人类热量摄入的直接数据。基于93代谢物谱的多变量模式识别分析可以区分自由进食（AL）和CR大鼠（训练集准确率为100%，测试集平均值>90%），并能够构建个体大鼠中间摄入量的准确模型（r2=0.88）。分析工作已将该特征用于人血浆。初始血清蛋白质组图谱也以100%的准确度区分饮食。目标是：（1）确定蛋白质组和代谢组在化合物、途径和谱水平上发生的时间变化。然后使用这些数据（a）确定干预前、干预期间和干预后（如果可能）与CR曲线的定量拟合，以及（B）定量评估大鼠中与进行性CR相关的沿着数学连续统的运动。(2)提供参与者血液中代谢组学和蛋白质组学成分的电子档案，可以重复挖掘，用于未来新假设的测试;（3）开发对人类短期和长期低热量饮食敏感的数学模型，用于补充PI实验室目前正在生成的疾病预测模型;（4）检查三个CALERIE站点的概况变化，以比较和对比观察到的变化。

DESCRIPTION (provided by applicant): Calorie Restriction (CR) is the most potent, robust, and reproducible known means of extending longevity and decreasing morbidity in lab rodents. Despite 70 years of research, the relevance of this observation for humans remains unknown. Relevance is supported by the established link between obesity and morbidity in humans. Potential linkages are being directly addressed by the NIH-sponsored CALERIE (comprehensive assessment of long-term effects of reducing intake of energy) study. This study will enroll approximately 250 individuals and collect blood samples at 6 time points over 24 months. Our proposed ancillary study has two goals: (A) to support CALERIE by characterizing the plasma metabolome and proteome in these samples; the initial foci being to determine if pre-existing metabolomic profiles, and proteomic profiles being developed in NIH funded studies, enable us to follow CR in people from three geographically distinct sites (thus linking human studies to the rodent literature) and to identify metabolites and pathways of interest, and; (B) to provide data grounding and linking the PI's ongoing studies of the use of metabolomic and proteomic profiles from CR rats to predict future disease risk for type II diabetes and breast cancer with direct data on human caloric intake. Multivariate pattern recognition analysis based on a 93 metabolite profile can distinguish ad libitum fed (AL) and CR rats (100% accuracy in training sets, mean >90% in test sets), and has enabled construction of accurate models of intermediate intakes (r2=0.88) for individual rats. Analytical work has adapted this profile for human plasma. Initial sera proteome profiles also distinguish diet with 100% accuracy. The AIMs are: (1) To determine temporal shifts that occur in the proteome and metabolome at the levels of compounds, pathways, and profiles. Then to use these data to (a) determine quantitative fit to a CR profile pre-, during, and, if possible, post- intervention, and; (b) quantitatively assess movement along a mathematical continuum related to progressive CR in rats. (2) To provide an electronic archive of the metabolomic and proteomic constituents of the blood of participants that could be repeatedly mined for future testing of new hypotheses; (3) To develop mathematical models sensitive to short and long-term low calorie diets in humans to be used in complement with models of disease prediction now being generated in the PIs lab, and; (4) To examine profile changes across the three CALERIE sites to compare and contrast observed changes.