Gene–environment interactions in the study of asthma in the postgenomewide association studies era. Issue 1 (February 2015)

• Record Type: Journal Article
• Authors: Rava, Marta; Smit, Lidwien A.M.; Nadif, Rachel
• Is Part Of: Current opinion in allergy and clinical immunology. Volume 15:Issue 1(2015:Feb.)
• Publication Date: 2015-02
• Subjects: asthma -- environmental exposure -- gene–environment interaction -- genomewide association studies; Allergy -- Periodicals; Clinical immunology -- Periodicals; Hypersensitivity; Immunity; Immune System Diseases; Allergy and Immunology; 616.079
• DOI: 10.1097/ACI.0000000000000131
• Languages: English
• ISSNs: 1528-4050

Abstract

Abstract : Purpose of review: Asthma is a complex disease characterized by an intricate interplay of both heritable and environmental factors. Understanding the mechanisms through which genes and environment interact represents one of the major challenges for pulmonary researchers. This review provides an overview of the recently published literature on gene–environment (G × E) interactions in asthma, with a special focus on the new methodological developments in the postgenomewide association studies (GWAS) era. Recent findings: Most recent studies on G × E interaction in asthma used a candidate-gene approach. Candidate-gene studies considering exposure to outdoor air pollutants showed significant interactions mainly with variants in the GSTP1 gene on asthma in children. G × E studies on passive and active smoking, including one genomewide interaction study, identified novel genes of susceptibility to asthma and a time-dependent effect of maternal smoking. Other recent studies on asthma found interactions between candidate genes and occupational allergen exposure and several domestic exposures such as endotoxin and gas cooking. New methods were developed to efficiently estimate G × E interaction in GWAS, and a pathway-based strategy to select an enriched gene-set for G × E studies has recently been proposed. Summary: The G × E studies presented in this review offer a good example on how candidate-gene approaches can complement and help in validating GWAS findings.