Use of biomarkers to identify phenotypes and endotypes of severe asthma

Tara F. Carr, Monica Kraft

Research output: Contribution to journalReview article

6 Citations (Scopus)

Abstract

Objective: Severe asthma can be classified into phenotypes and endotypes, which may inform clinicians about inflammatory pathways leading to disease and ultimately guide optimal therapeutic strategy. Biomarkers, objectively measurable characteristics of the disease, are of increasing interest to clinicians and researchers as powerful tools to distinguish among the severe asthma phenotypes and endotypes. The objective of this review is to highlight current knowledge of biomarker applications to identify phenotypes and endotypes of severe asthma. Data Sources: Sources used include observational cohorts, clinical trials, translational studies, comprehensive reviews, and expert/taskforce statements. Study Selections: Included studies were selected for their relevance to the topic and for strength of data or study design. Results: In severe asthma, biomarkers can be used for diagnosis of phenotype or endotype, can also be predictive of clinical outcomes or response to therapy, and may be dynamic with time or therapy. Fully determining phenotype or endotype of severe asthma will require interpretation of combinations of commercially available biomarkers. Conclusion: Biomarkers have multiple potential clinical applications in severe asthma. Novel biomarkers may add accuracy to this field.

Original languageEnglish (US)
Pages (from-to)414-420
Number of pages7
JournalAnnals of Allergy, Asthma and Immunology
Volume121
Issue number4
DOIs
StatePublished - Oct 2018

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Asthma
Biomarkers
Phenotype
Information Storage and Retrieval
Therapeutics
Research Personnel
Clinical Trials

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Pulmonary and Respiratory Medicine

Cite this

Use of biomarkers to identify phenotypes and endotypes of severe asthma. / Carr, Tara F.; Kraft, Monica.

In: Annals of Allergy, Asthma and Immunology, Vol. 121, No. 4, 10.2018, p. 414-420.

Research output: Contribution to journalReview article

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