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The use of pharmacogenomics, epigenomics, and transcriptomics to improve childhood asthma management: Where do we stand?
Author(s) -
Farzan Niloufar,
Vijverberg Susanne J.,
Kabesch Michael,
Sterk Peter J.,
Maitlandvan der Zee Anke H.
Publication year - 2018
Publication title -
pediatric pulmonology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.866
H-Index - 106
eISSN - 1099-0496
pISSN - 8755-6863
DOI - 10.1002/ppul.23976
Subject(s) - pharmacogenomics , epigenomics , medicine , asthma , endotype , disease , population , bioinformatics , mechanism (biology) , precision medicine , intensive care medicine , immunology , dna methylation , genetics , gene , pharmacology , biology , gene expression , pathology , philosophy , environmental health , epistemology
Asthma is a complex multifactorial disease and it is the most common chronic disease in children. There is a high variability in response to asthma treatment, even in patients with good adherence to maintenance treatment, and a correct inhalation technique. Distinct underlying disease mechanisms in childhood asthma might be the reason of this heterogeneity. A deeper knowledge of the underlying molecular mechanisms of asthma has led to the recent development of advanced and mechanism‐based treatments such as biologicals. However, biologicals are recommended only for patients with specific asthma phenotypes who remain uncontrolled despite high dosages of conventional asthma treatment. One of the main unmet needs in their application is lack of clinically available biomarkers to individualize pediatric asthma management and guide treatment. Pharmacogenomics, epigenomics, and transcriptomics are three omics fields that are rapidly advancing and can provide tools to identify novel asthma mechanisms and biomarkers to guide treatment. Pharmacogenomics focuses on variants in the DNA, epigenomics studies heritable changes that do not involve changes in the DNA sequence but lead to alteration of gene expression, and transcriptomics investigates gene expression by studying the complete set of mRNA transcripts in a cell or a population of cells. Advances in high‐throughput technologies and statistical tools together with well‐phenotyped patient inclusion and collaborations between different centers will expand our knowledge of underlying molecular mechanisms involved in disease onset and progress. Furthermore, it could help to select and stratify appropriate therapeutic strategies for subgroups of patients and hopefully bring precision medicine to daily practice.