The effects of immune-age on immune-response and the molecular mechanisms which drive it

项目总结 免疫系统是一个复杂的系统，随着它对内部和外部的反应而不断变化 环境，这使得很难理解个体和其功能之间的差异 这意味着什么。我们的SELA得出的轨迹捕捉到了个体之间免疫细胞组成的变化， 从而描述了在健康衰老过程中细胞组成变化的保守级联。一个 个体的高维免疫细胞组成可以转化为描述 它在免疫老化级联中的位置反映了免疫年龄。个体的免疫年龄随着他们的变化而改变 沿着这种有模式的轨迹以不同的速度前进，导致基线处个体间的高度差异。 我们假设，由于表观遗传细胞的特异性，免疫老化轨迹在个体之间是保守的。 通过与常见的生理和环境变化相互作用而引起的变化 随着年龄增长而发生。此外，我们假设这是个体间免疫年龄的基线差异。 在免疫反应过程中有功能影响，最终可能导致临床结果的可变性， 这在大多数侮辱和治疗中都是遵守的。项目1旨在丰富和完善我们的免疫力 通过扩大我们的队列(增加40-60岁的双胞胎)和通过测量额外的免疫细胞来衡量年龄 发现与免疫相关的类型、因素(细胞因子、表观遗传修饰和代谢组学) 衰老。此外，我们将确定推动免疫年龄轨迹进展的因素。此外, 我们将全面了解年龄和免疫史如何影响适应性(B和T)反应 在老年人中引发每年接种流感疫苗。最后，利用12年生物银行储存的SELA样本 在季节性流感疫苗接种前后，我们将检验分子免疫反应不同的假设 作为不同疫苗引起的基线免疫年龄和去耦合免疫动力学的函数 由免疫年龄引起的成分。我们将结合后一种分子特征 与免疫年龄相关的流感特异性适应反应数据首次获得 全面了解老年人的疫苗反应，老年人是感染的风险群体。我们希望 将免疫年龄与B型和T型流感病史相结合，将允许从基线预测流感疫苗反应， 这是一个高度关注世界卫生的悬而未决的问题。

PROJECT SUMMARY The immune system is a complex system which continuously changes as it responds to the internal and external environments, making it very difficult to understand the variation between individuals and its functional implications. Our SELA derived trajectory captures the variation in immune-cell composition between individuals, thus describes the conserved cascade of cell compositional changes occurring during healthy aging. An individual’s high-dimensional immune cell composition can be translated into a quantitative measure describing its position along this immune-aging cascade reflecting the immune-age. Individuals’ immune-age alters as they advance at different rates along this patterned trajectory, resulting in high inter-individual variation at baseline. We hypothesize that the immune-aging trajectory is conserved between individuals due to epigenetic cell-specific alterations that are induced through an interaction with common physiological and environmental changes that occur with age. Furthermore, we hypothesize that this the baseline variation in immune-age between individuals has functional implications during immune response, which ultimately may lead to variability in clinical outcome, which is observed for the majority of insults and therapies. Project 1 is designed to enrich and refine our immune age metric by expanding our cohort (adding 40-60 years-old twins) and by measuring in addition immune cell types, factors (cytokines, epigenetic modifications, and metabolomics) found to be in correlation with immune aging. Furthermore, we will identify factors that drive progression along the immune age trajectory. In addition, we will gain comprehensive insight into the way age and immune history affect adaptive (B and T) responses elicited by annual influenza vaccination in the old. Lastly, leveraging the 12+ years of bio-banked SELA samples pre and post seasonal influenza vaccination we will test the hypothesis that molecular immune responses differ as a function of baseline immune-age and decouple immune dynamics that are caused by different vaccine compositions from those that are caused by immune-age. We will combine the latter molecular features correlated with immune age with data on flu specific adaptive responses to obtain, for the first-time comprehensive understanding of vaccine responses in older adults, a risk group for infection. We hope that combining immune-age with B and T flu history, will allow to predict influenza vaccine response from baseline, an unsolved problem of high concern for world health.