1. Academic Validation
  2. Leveraging -omics for asthma endotyping

Leveraging -omics for asthma endotyping

  • J Allergy Clin Immunol. 2019 Jul;144(1):13-23. doi: 10.1016/j.jaci.2019.05.015.
Scott R Tyler 1 Supinda Bunyavanich 2
Affiliations

Affiliations

  • 1 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
  • 2 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY; Division of Allergy and Immunology, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY. Electronic address: supinda@post.harvard.edu.
Abstract

Asthma is a highly heterogeneous disease, often manifesting with wheeze, dyspnea, chest tightness, and cough as prominent symptoms. The eliciting factors, natural history, underlying Molecular Biology, and clinical management of asthma vary highly among affected subjects. Because of this variation, many efforts have gone into subtyping asthma. Endotypes are subtypes of disease based on distinct pathophysiologic mechanisms. Endotypes can be clinically useful because they organize our mechanistic understanding of heterogeneous diseases and can direct treatment toward modalities that are likely to be the most effective. Asthma endotyping can be shaped by clinical features, laboratory parameters, and/or -omics approaches. We discuss the application of -omics approaches, including transcriptomics, epigenomics, microbiomics, metabolomics, and proteomics, to asthma endotyping. -Omics approaches have provided supporting evidence for many existing endotyping paradigms and also suggested novel ways to conceptualize asthma endotypes. Although endotypes based on single -omics approaches are relatively common, their integrated multi-omics application to asthma endotyping has been more limited thus far. We discuss paths forward to integrate multi-omics with clinical features and laboratory parameters to achieve the goal of precise asthma endotypes.

Keywords

-ome; -omic; Asthma; cluster; endotype; epigenome; integrate; metabolome; microbiome; multi-ome; phenotype; proteome; transcriptome.

Figures