Immune Responses to Influenza Vaccination

精确模型的发展允许对扰动的生物反应进行预测，这有可能增加我们对病理生理学的机制理解，并有助于改进治疗方法的发展。人类免疫系统为开发此类系统生物学方法提供了极好的环境：许多免疫细胞和分子成分很容易从血液中获得，允许从多个时间点的个体收集样本，然后进行深入的数据生成和分析。此外，越来越多的人认识到免疫系统和炎症有助于多种疾病的发病机制。这些疾病不仅包括那些通常被认为与免疫系统有关的疾病，如自身免疫性疾病和传染病，还包括癌症、心脏病、糖尿病、肥胖症、神经退行性疾病和其他影响很大一部分人口的慢性疾病（Germain和Schwartzberg， Nat Immunol. 2011）。因此，更全面和定量地了解免疫反应是如何协调的，以及确定有效反应与破坏性反应的预测性分子和细胞参数，可能对预防和治疗各种疾病具有重大意义。为此，我帮助协调了美国国立卫生研究院人类免疫学中心的一项初步研究，该研究旨在帮助建立正常人类变异（人类免疫组）的数据库，并了解免疫状态的变异如何促进免疫反应和疾病（Tsang， Schwartzberg等人，Cell 2014; DIckler， H.等人，Ann New York Acad Sci, 2013）。

The development of accurate models that permit prediction of biological responses upon perturbation has the potential to increase our mechanistic understanding of pathophysiology and contribute to the development of improved therapeutics. The human immune system provides an excellent context for developing such systems biology approaches: many immune cells and molecular components are readily accessible from blood, permitting collection of samples from individuals across multiple time-points, followed by in depth data generation and analyses. Furthermore, there is an increasing understanding that the immune system and inflammation contribute to the pathogenesis of multiple disorders. These include not only those classically considered to involve the immune system such as autoimmune and infectious diseases, but also cancer, cardiac disease, diabetes, obesity, neurodegeneration, and other chronic illnesses affecting a large segment of the population (Germain and Schwartzberg, Nat Immunol. 2011). Thus, a more comprehensive and quantitative understanding of how immune responses are orchestrated, together with identification of predictive molecular and cellular parameters of effective vs. damaging responses, could have major implications for the prevention and treatment of diverse diseases. To this end, I helped coordinate one of the initial studies from the NIH Center for Human Immunology designed to help build a data base of normal human variation (the human immunome) and understand how variation in immune states contributes to immune reponses and disease (Tsang, Schwartzberg et al, Cell 2014; DIckler, H. et al, Ann New York Acad Sci, 2013). We are now conducting a follow-up study comparing responses to both an unadjuvented and an adjuvented vaccine against Influenza H5N1. To complement our work, we have added new assays characterizing follicular T helper cells, a key T cell population that helps B cells make long-term antibody responses. We are using these approaches to look at responses to immunization in greater depth and to optimize technical and scientific approaches to better understand vaccines. Bioinformatic analyses of these data are in progress.