Making it big in allergy

Abstract

Historically, clinical care and scientific approaches have focused on individual components. However, this strategy has limitations, such as the inability to identify the interconnecting pathways that control immune responses, and does not reveal how the immune system works across multiple biological systems and scales. Today, modern technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune system function. Although the term causes some established systems biologists to cringe, ‘‘big data’’ creates new challenges and opportunities for the study of allergic disease. Approaches that aim to integrate different quantitative and qualitative measurements into a holistic model that can be applied prospectively to predict phenotypic outcomes and the effect of various perturbations on a system of interest can be broadly classified within the field of systems biology. Using an iterative process of quantitative sampling, computational modeling, and experimental testing of proposed hypotheses, systems biology– based analysis has the potential to transform our understanding of the complexity of the immune system. Innovators established the field of systems biology as we know it today by developing the necessary ‘‘-omics’’ technologies, sequencing the first genomes, and developing the first mathematic models of gene regulation and other processes. Many of these same leaders presently direct teams that push the boundaries of systems biology in the study of many organisms, biological processes, and clinical phenotypes. Although still in its nascent stages, the application of systems biology to allergic diseases is a highly encouraging pursuit. An auspicious direction is offered by the integration of genomeand immunome-wide data sets from sources such as ENCODE, Roadmap Epigenomics, the Human