Systems biology of asthma and allergic diseases: a multiscale approach

J Allergy Clin Immunol. 2015 Jan;135(1):31-42. doi: 10.1016/j.jaci.2014.10.015. Epub 2014 Nov 21.


Systems biology is an approach to understanding living systems that focuses on modeling diverse types of high-dimensional interactions to develop a more comprehensive understanding of complex phenotypes manifested by the system. High-throughput molecular, cellular, and physiologic profiling of populations is coupled with bioinformatic and computational techniques to identify new functional roles for genes, regulatory elements, and metabolites in the context of the molecular networks that define biological processes associated with system physiology. Given the complexity and heterogeneity of asthma and allergic diseases, a systems biology approach is attractive, as it has the potential to model the myriad connections and interdependencies between genetic predisposition, environmental perturbations, regulatory intermediaries, and molecular sequelae that ultimately lead to diverse disease phenotypes and treatment responses across individuals. The increasing availability of high-throughput technologies has enabled system-wide profiling of the genome, transcriptome, epigenome, microbiome, and metabolome, providing fodder for systems biology approaches to examine asthma and allergy at a more holistic level. In this article we review the technologies and approaches for system-wide profiling, as well as their more recent applications to asthma and allergy. We discuss approaches for integrating multiscale data through network analyses and provide perspective on how individually captured health profiles will contribute to more accurate systems biology views of asthma and allergy.

Keywords: Systems biology; allergy; asthma; atopic; big data; epigenome; genome; individual health profile; metabolome; microbiome; network; transcriptome.

Publication types

  • Review

MeSH terms

  • Animals
  • Genome
  • Humans
  • Hypersensitivity* / genetics
  • Hypersensitivity* / metabolism
  • Hypersensitivity* / microbiology
  • Metabolome
  • Microbiota
  • Systems Biology*
  • Transcriptome