Identification of blood biomarkers predictive of organ aging

项目摘要 随着年龄的增长，我们的组织和器官会经历分子和生理损伤， 功能正常，最终导致疾病状态。这些变化不仅是由于老龄化 过程本身，但在很大程度上受到包括所有非遗传暴露在内的麻烦的影响 （环境和行为）。取决于个体的烦恼与 不同的器官随着时间的推移以不同的速度恶化，导致组织具有不同的 同一个体的生物学年龄。由于给定器官的生物年龄反映了其整体健康状况， 功能能力，生物学上较老的器官更容易引起健康问题， 疾病由组学技术（转录组学、蛋白质组学、表观基因组学等）驱动的衰老“时钟”和 机器学习方法已被用于估计特定组织的生物年龄。然而，在这方面， 组织特异性时钟需要来自活组织检查的组学数据，使得临床采用不切实际。因此有 迫切需要开发简单的诊断工具，使用容易获得的生物材料来测量器官- 具体的老化率在个人，可以转化为个性化的actionabilities，并使准确的 评估促进健康的干预措施的效力。利用血液，免疫系统的管道， 我们和其他人已经证明，加速老化，如年龄相关的， 慢性炎症和免疫系统功能障碍，导致器官功能障碍， 老年受试者的疾病风险增加。这并不奇怪，因为炎症被认为是一种 大多数（如果不是全部）衰老疾病的共同点。在这个提议中，我们假设生物学 研究给定器官的老化速率的信息包含在同一个体的血液中， 因此，可以使用一组组织特异性基因表达标记来估计，这些标记与来自 血液样本在这里，我们将在NIH公共数据库内外组装多个公共领域数据集。 基金用于创建基于血液的器官特异性时钟，并能够快速诊断给定器官的老化率 在一个人身上。为此，我们将使用多个组织的转录组学数据和匹配的血液， 基因型-组织表达（GTEx）数据库构建计算框架， 一个人的45个组织的老化的血液基因表达。我们将验证生成的模型， 预测器官特异性衰老在特定于感兴趣器官的疾病状态下，我们将评估其影响。 生活方式因素，包括饮食，运动和吸烟对不同器官衰老的影响， 心脏病研究。最后，我们将使用基于集成网络的蜂窝签名库 （LINCS），以确定候选化合物，可以恢复基因表达的变化，在血液相关的 组织老化到最佳水平。

Project Summary As we age, our tissues and organs experience molecular and physiological damage that prevents them from functioning properly and this ultimately leads to disease states. These changes are not only due to the aging process itself but are largely influenced by the exposome which includes all non-genetic exposures (environmental and behavioral). Depending on the complex interaction between the exposome of an individual and their genetics, different organs deteriorate over time at a different pace, resulting in tissues with different biological ages within the same individual. As the biological age of a given organ reflects its overall health and functional capacity, biologically older organs are more likely to cause health problems increasing the risk of diseases. Aging “clocks” powered by omics technologies (transcriptomics, proteomics, epigenomics, etc.) and machine learning methods have been used to approximate the biological age of specific tissues. However, tissue-specific clocks require omics data from a biopsy, making clinical adoption impractical. Therefore, there is a critical need to develop simple diagnostic tools using readily accessible biological material to measure organ- specific aging rates in an individual which can be translated into personalized actionabilities and enable accurate evaluation of the efficacy of health-promoting interventions. Using blood, the pipeline of the immune system, from aging cohorts we and others have demonstrated that accelerated aging, as evidenced by age-related chronic inflammation (inflammaging) and dysfunctional immune systems, results in organ dysfunction and an elevated risk of disease in older subjects. This is not surprising since inflammaging has been proposed to be a common denominator of most, if not all, diseases of aging. In this proposal, we hypothesize that the biological information to investigate the aging rates of a given organ is contained in the blood of the same individual and thus, can be estimated using a collection of tissue-specific gene expression signatures matched with those from blood samples. Here, we will assemble multiple public domain datasets within and outside of the NIH Common Fund to create blood-based organ-specific clocks and enable rapid diagnostics of aging rates for a given organ in an individual. To do so, we will use transcriptomic data across multiple tissues and matched blood from the Genotype-Tissue Expression (GTEx) database to construct a computational framework that calculates the rate of aging of 45 tissues in an individual using blood gene expression. We will validate the resulting models to predict organ-specific aging in disease states specific to the organ of interest, and we will assess the influence of lifestyle factors including diet, exercise and smoking on the aging of different organs using data from the Framingham Heart Study. Finally, we will use the Library of Integrated Network-based Cellular Signatures (LINCS) to identify candidate compounds that can restore the gene expression changes in the blood associated with tissue aging to optimal levels.