Identification of blood biomarkers predictive of organ aging

鉴定预测器官衰老的血液生物标志物

• 批准号: 10777065
• 负责人: David Furman
• 金额: $ 38.8万
• 依托单位: BUCK INSTITUTE FOR RESEARCH ON AGING
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-20 至 2024-09-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10777065
• 关键词: Acceleration; Activities of Daily Living; Adoption; Age; Aging; Behavioral; Biocompatible Materials; Biological; Biological Clocks; Biological Markers; Biopsy; Blood; Blood specimen; Cardiovascular Diseases; Chronic; Clinic; Clinical; Clinical Data; Clinical Trials; Cohort Studies; Complex; Cost Savings; Coupled; Cues; Data; Data Set; Databases; Deterioration; Development; Diagnostic tests; Diet; Disease; Early Diagnosis; Environment; Exercise; Framingham Heart Study; Functional disorder; Funding; Future; Gene Expression; Gene Expression Profile; General Population; Generations; Genes; Genetic; Genotype; Goals; Health; Health Personnel; Health Promotion; Healthcare Systems; Immune system; Incidence; Individual; Inflammaging; Inflammation; Inflammatory; Intervention; Libraries; Life Style; Longevity; Malignant Neoplasms; Measures; Modeling; Molecular; Network-based; Neurodegenerative Disorders; Nutritional; Organ; Outcome; Pathologic Processes; Patients; Pharmaceutical Preparations; Physiological; Predictive Value; Procedures; Process; Proteomics; Public Domains; Public Health; Rapid diagnostics; Research; Residual state; Series; Smoking; Smoking Status; Techniques; Technology; Testing; Time; Tissue Banks; Tissue Sample; Tissue-Specific Gene Expression; Tissues; Translating; United States National Institutes of Health; age related; candidate identification; clinically relevant; cohort; computer framework; diagnostic tool; disorder risk; drug repurposing; effectiveness evaluation; efficacy evaluation; epigenomics; experience; human data; human subject; improved; insight; interest; lifestyle factors; machine learning method; machine learning prediction; new technology; non-genetic; pharmacologic; predictive marker; prevent; preventive intervention; repository; technology platform; therapy development; tool; transcriptomics

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.

项目摘要 随着年龄的增长，我们的组织和器官会遭受分子和物理损害，从而阻止它们 正常运作，这最终导致疾病状态。这些变化不仅是由于老化 过程本身，但在很大程度上受到暴露体的影响，包括所有非遗传暴露 （环境和行为）。取决于个人的释放组之间的复杂相互作用 及其遗传学，不同的器官随着时间的流逝而在不同的速度下检测到，导致组织不同 同一个人的生物年龄。随着给定器官的生物年龄反映了其整体健康状况 功能能力，生物学上年龄较大的器官更有可能导致健康问题，从而增加 疾病。衰老的“时钟”由OMICS技术（转录组学，蛋白质组学，表观基因组学等）提供支持）和 机器学习方法已用于近似特定组织的生物年龄。然而， 组织特异性时钟需要活检中的OMICS数据，使临床采用不切实际。因此，有 使用易于访问的生物学材料来制定简单诊断工具的迫切需要，以测量器官 个人的特定老化率可以转化为个性化的行动能力并启用准确 评估促进健康干预措施的效率。使用血液，免疫系统的管道， 从衰老队列中，我们和其他人证明了加速衰老，这是与年龄相关的 慢性炎症（炎症）和功能失调的免疫系统，导致器官功能障碍和 老年受试者的疾病风险升高。这并不奇怪，因为已经提出炎症是 大多数（如果不是全部）衰老疾病的共同点。在此提案中，我们假设生物学 调查给定器官的衰老率的信息包含在同一个人的血液中， 因此，可以使用与来自 血液样本。在这里，我们将在NIH Common内外组装多个公共领域数据集 基金创建基于血液的器官特定时钟，并能够快速诊断给定器官的老化率 在个人。为此，我们将使用多个时间安排的转录组数据，并匹配来自 基因型 - 组织表达（GTEX）数据库，以构建计算速率的计算框架 使用血液基因表达在一个人中45个组织的老化。我们将验证结果模型 预测特定于感兴趣器官的疾病状态的器官特异性衰老，我们将评估影响 生活方式因素包括饮食，运动和吸烟在不同的器官衰老上使用来自 弗雷明汉心学习。最后，我们将使用基于网络的集成蜂窝签名的库 （lincs）识别可以恢复基因表达的候选化合物，与血液相关的血液变化 组织老化至最佳水平。