The current state of omics technologies in the clinical management of asthma and allergic diseases

Ann Allergy Asthma Immunol. 2019 Dec;123(6):550-557. doi: 10.1016/j.anai.2019.08.460. Epub 2019 Sep 5.

Abstract

Objective: To review the state of omics science specific to asthma and allergic diseases and discuss the current and potential applicability of omics in clinical disease prediction, treatment, and management.

Data sources: Studies and reviews focused on the use of omics technologies in asthma and allergic disease research and clinical management were identified using PubMed.

Study selections: Publications were included based on relevance, with emphasis placed on the most recent findings.

Results: Omics-based research is increasingly being used to differentiate asthma and allergic disease subtypes, identify biomarkers and pathological mediators, predict patient responsiveness to specific therapies, and monitor disease control. Although most studies have focused on genomics and transcriptomics approaches, increasing attention is being placed on omics technologies that assess the effect of environmental exposures on disease initiation and progression. Studies using omics data to identify biological targets and pathways involved in asthma and allergic disease pathogenesis have primarily focused on a specific omics subtype, providing only a partial view of the disease process.

Conclusion: Although omics technologies have advanced our understanding of the molecular mechanisms underlying asthma and allergic disease pathology, omics testing for these diseases are not standard of care at this point. Several important factors need to be addressed before these technologies can be used effectively in clinical practice. Use of clinical decision support systems and integration of these systems within electronic medical records will become increasingly important as omics technologies become more widely used in the clinical setting.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Computational Biology*
  • Environmental Exposure
  • Humans
  • Hypersensitivity* / genetics
  • Hypersensitivity* / metabolism
  • Hypersensitivity* / microbiology
  • Hypersensitivity* / therapy