Serum Metabolomic/Proteomic Profiles in CALERIE

描述(由申请人提供)： 卡路里限制(CR)是已知的延长实验啮齿动物寿命和降低发病率的最有效、最健壮和最可重复的方法。尽管进行了70年的研究，但这一观察结果与人类的相关性仍然不得而知。肥胖症与人类发病率之间已确立的联系也支持了这一相关性。NIH赞助的CALERIE(减少能量摄入的长期影响综合评估)研究直接解决了潜在的联系。这项研究将招募大约250人，并在24个月的6个时间点收集血液样本。我们拟议的辅助研究有两个目标：(A)通过鉴定这些样本中的血浆代谢组和蛋白质组来支持CALERIE；最初的重点是确定先前存在的代谢组谱和NIH资助的研究中正在开发的蛋白质谱是否能够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；以及(B)提供数据基础，并将PI正在进行的利用大鼠代谢组和蛋白质组来预测II型糖尿病和乳腺癌的未来疾病风险的研究与人类热量摄入的直接数据联系起来。基于93代谢物图谱的多变量模式识别分析可以区分随意喂养(AL)和CR大鼠(训练组准确率为100%，测试组为90%)，并能够为单个大鼠建立准确的中间摄入量模型(R2=0.88)。分析工作使这一图谱适用于人类血浆。最初的血清蛋白质组图谱也以100%的准确性区分饮食。其目的是：(1)确定蛋白质组和代谢组在化合物、途径和轮廓水平上发生的时间变化。然后使用这些数据来(A)确定干预前、干预期间和(如果可能的话)干预后CR图谱的定量适配性，以及(B)定量评估与进行性CR相关的数学连续体的运动。(2)提供参与者血液的代谢组和蛋白质组组成的电子档案，以便为未来的新假说测试而重复挖掘；(3)开发对人类短期和长期低卡路里饮食敏感的数学模型，以与PIS实验室目前生成的疾病预测模型相辅相成；以及(4)检查CALERIE三个地点的轮廓变化，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.