Unbiased identification of interventions that extend lifespan

项目摘要/摘要 主要模式生物的寿命可以通过饮食、药物和遗传干预来延长。 这包括老鼠模型，目前有超过15种已知的长寿干预措施。 然而，这些治疗方法是在个案方法上确定的。他们之间的关系 不清楚，也不知道它们是通过相同还是不同的机制起作用，以及哪些干预措施是 最有效和最健壮的。因此，有必要对长寿进行系统、公正的鉴定 对哺乳动物的干预。要从延长老鼠的寿命过渡到在人类身上延长寿命，这一点很重要 既要确定许多延长寿命的干预措施，又要确定寿命控制的一般原则。在这 考虑到，细胞或有机体寿命更短或更长的潜力由其新陈代谢状态来表示， 这反过来又反映在它的转录组中。以某种方式调整转录组的干预 可能会将生物体从较短的寿命状态转变为较长的寿命状态。我们定义了基因表达的这种变化 作为长寿的标志，并对它们进行了描述：(I)不同于30岁的哺乳动物的肝、肾和脑- 寿命延长；(Ii)已知可延长小鼠寿命的干预措施；以及(Iii)细胞类型不同的人类细胞 营业额。使用这些签名，我们预测并验证了具有潜在寿命的化合物 分机。我们建议直接在小鼠身上测试这些候选长寿干预措施对寿命的影响 并将此方法扩展到基于高级寿命签名和 确定额外的长寿干预措施。因此，我们提出了两个主要的研究方向：(I) 小鼠长寿干预措施的鉴定和验证。我们将首先测试50种化合物对 然后将测试表现最好的20种化合物对寿命的影响。我们会 还分析了成功的长寿干预措施所针对的机制和途径，以及 整合这些信息以定义寿命控制原则。(2)不偏不倚的身份识别平台 延长寿命的干预措施。我们将首先开发高级长寿签名，基于分析 基因表达、代谢物特征及其在三种延长寿命模型中的整合 (哺乳动物的长寿、细胞类型的长寿和老鼠干预)。然后，这些签名将用于 预测延长寿命的化合物，这将通过基因表达和分析来验证 生物学年龄。最后，我们将建立一个筛选化合物和其他干预措施的平台，并确定 广泛的长寿干预措施。在项目完成时，我们将知道哪种长寿 签名是延长寿命干预措施的最佳预测指标，确定调节其效果的途径， 了解寿命是如何管理的，开发一个确定长寿干预措施的平台，以及 找出一些可以延缓老鼠衰老的新制剂。有了这些信息，就可以为未来的考试设计 对人类长寿干预措施的测试。

PROJECT SUMMARY/ABSTRACT Lifespan of major model organisms can be extended by dietary, pharmacological and genetic interventions. This includes mouse models, for which there are currently more than 15 known longevity interventions. However, these treatments have been identified on a case-by-case approach. The relationship between them is unclear and it is not known if they act through the same or different mechanisms and which interventions are most effective and robust. Accordingly, there is a need for systematic, unbiased identification of longevity interventions in mammals. To transition from extending lifespan in mice to doing this in humans, it is important to both identify many interventions that extend lifespan and define general principles of lifespan control. In this regard, the potential of the cell or organism to live a shorter or longer life is represented by it’s metabolic state, which in turn is reflected in it’s transcriptome. An intervention that adjusts the transcriptome in a certain way may shift an organism from a shorter-lived to a longer-lived state. We define such changes in gene expression as longevity signatures and have described them for (i) liver, kidney and brain across mammals differing 30- fold in lifespan; (ii) interventions known to extend lifespan in mice; and (iii) human cell types differing in cell turnover. Using these signatures, we then predicted and validated compounds with potential for lifespan extension. We propose to directly test these candidate longevity interventions in mice for the effect on lifespan and extend this approach to define principles of lifespan control based on advanced longevity signatures and identification of additional longevity interventions. Accordingly, we propose two broad research directions: (i) Identification and validation of longevity interventions in mice. We will first test 50 compounds for the effect on biological age in mice and then will test the 20 best-performing compounds for the effect on lifespan. We will also analyze successful longevity interventions with regard to mechanisms and pathways they target, and integrate this information to define principles of lifespan control. (ii) Platform for unbiased identification of interventions that extend lifespan. We will first develop advanced longevity signatures, based on the analyses of gene expression, metabolite profiling and their integration across three models of increased lifespan (longevity of mammals, longevity of cell types, and mouse interventions). Then, the signatures will be used to predict compounds that extend lifespan, which will be validated through gene expression and assays of biological age. Finally, we will build a platform for screening of compounds and other interventions and identify a broad range of longevity interventions. At the completion of the project, we will know which longevity signatures are best predictors of lifespan-extending interventions, identify pathways that mediate their effects, understand how lifespan is regulated, develop a platform for the identification of longevity interventions, and identify a number of new agents that slow mouse aging. With this information, tests can be designed for future testing of longevity interventions in humans.