A life course perspective on gut microbiome aging and health in a non-human primate model

非人类灵长类动物模型中肠道微生物组衰老和健康的生命历程视角

• 批准号: 10392998
• 负责人: Elizabeth Archie
• 金额: $ 64.26万
• 依托单位: UNIVERSITY OF NOTRE DAME
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10392998
• 关键词: Acceleration; Activities of Daily Living; Adult; Affect; Age; Aging; Animal Model; Behavioral; Biodiversity; Biological; Biological Aging; Birth; Cessation of life; Clinical; Collection; Complement; Consensus; Data; Data Set; Development; Diabetes Mellitus; Disease; Elderly; Environmental Risk Factor; Genes; Health; Human; Individual; Individual Differences; Inflammation; Intervention; Kenya; Lead; Learning; Life; Life Cycle Stages; Link; Logistics; Longevity; Malnutrition; Measures; Metabolic Pathway; Microbe; Microbial Taxonomy; Mission; Modeling; Morbidity - disease rate; Nature; Obesity; Osteoporosis; Outcome; Papio; Pathway interactions; Pattern; Personal Satisfaction; Persons; Physiology; Population; Population Research; Primates; Probiotics; Process; Prospective Studies; Research; Risk; Sampling; Social Conditions; Social status; System; Taxonomy; Testing; Time; Variant; age related; base; comparative; density; design; early life adversity; frailty; gut microbiome; healthy aging; human old age (65+); improved; individual variation; longitudinal dataset; metagenome; microbial; microbiome; microbiome analysis; mortality; nonhuman primate; prospective; senescence; social; social factors

PROJECT SUMMARY The gut microbiome has repeatedly been linked to major diseases of aging, including frailty, osteoporosis, and diabetes. However, after more than a decade of searching, there is still no consensus on which microbial species or taxonomic features provide reliable hallmarks of aging in adults or the elderly. Different people harbor different collections of microbes with densities and dynamics that vary considerably from one person to the next. This personalization arises, in part, because a given microbe may perform different functions in different people, and even in the same person at different times. This variability constrains the utility of microbiome taxa (e.g. species, phyla, biodiversity) to measure health and healthy aging. Overcoming this hurdle requires a shift in strategy, away from taxonomic data and towards data types that reflect the gut microbiome’s functional capacities, including the microbial genes and metabolic pathways found in the gut microbiome’s metagenome. Developing gut microbiome markers of healthy aging will also require prospective, longitudinal population-based research. However, we lack prospective data sets that track longitudinal changes in individual gut microbiome function and health outcomes across adulthood and old age. Our objectives in this proposal are to use a prospective, full life course, nonhuman primate model to: (i) identify changes in the microbiome’s functional capacities across the life course; (ii) test how social and environmental factors affect the nature and pace of microbiome aging; (iii) test how taxa-function relationships change at different life stages; and (iv) learn which microbiome features predict physical/behavioral aging and all-cause mortality. Our system, the well-studied Amboseli baboon population in Kenya, captures the complexity of human behavioral and social conditions better than other animal models. We have already profiled gut microbial taxonomic composition in 17,277 fecal samples collected over 14 years from 501 baboons. These data reveal personalized microbiome dynamics and aging trajectories that are shaped by individual social and environmental conditions. We propose to expand this data set for 10 more years to include 800 total individuals and analyze microbiome functional capacity in 12,000 samples. By identifying drivers and patterns of microbiome functional aging, we will identify targets for interventions aimed at building and sustaining healthy aging. Our results will help harness the promise of the gut microbiome to predict and improve human health.

项目概要 肠道微生物组一再与主要的衰老疾病相关，包括虚弱、骨质疏松症、 和糖尿病。然而，经过十多年的探索，对于哪种微生物仍然没有达成共识。 物种或分类学特征提供了成年人或老年人衰老的可靠标志。不同的人 拥有不同的微生物群，其密度和动态因人而异 下一个。这种个性化的出现部分是因为特定的微生物可能在不同的环境中执行不同的功能。 不同的人，甚至同一个人不同的时间。这种可变性限制了 微生物组分类群（例如物种、门、生物多样性）来衡量健康和健康老龄化。克服这个 障碍需要策略的转变，从分类数据转向反映肠道的数据类型 微生物组的功能，包括肠道中发现的微生物基因和代谢途径 微生物组的宏基因组。开发健康衰老的肠道微生物标记物还需要前瞻性、 基于人群的纵向研究。然而，我们缺乏跟踪纵向变化的前瞻性数据集 成年期和老年期的个体肠道微生物组功能和健康结果。 我们在本提案中的目标是使用前瞻性的、完整生命历程的非人类灵长类动物模型来：（i） 确定微生物组在整个生命过程中功能的变化； (ii) 测试社交和 环境因素影响微生物组衰老的性质和速度； (iii) 测试分类单元与功能之间的关系 不同人生阶段的变化； (iv) 了解哪些微生物组特征可以预测身体/行为衰老以及 全因死亡率。我们的系统对肯尼亚的安博塞利狒狒种群进行了充分研究，捕捉到了 人类行为和社会条件的复杂性比其他动物模型更好。我们已经 14 年来从 501 份粪便样本中收集的 17,277 份粪便样本中的肠道微生物分类组成分析 狒狒。这些数据揭示了个性化的微生物组动态和衰老轨迹，这些轨迹是由 个人的社会和环境条件。我们建议将该数据集再扩展 10 年 总共包括 800 名个体，并分析 12,000 个样本中的微生物组功能能力。通过识别 微生物组功能老化的驱动因素和模式，我们将确定旨在建立干预措施的目标 和维持健康的老龄化。我们的结果将有助于利用肠道微生物组来预测和 改善人类健康。