Genetic risk factors for the development of allergic disease identified by genome-wide association
Portelli, M.A. and Hodge, Emily and Sayers, Ian (2015) Genetic risk factors for the development of allergic disease identified by genome-wide association. Clinical & Experimental Allergy, 45 (1). pp. 21-31. ISSN 1365-2222
Official URL: http://dx.doi.org/10.1111/cea.12327
An increasing proportion of the worldwide population is affected by allergic diseases such as allergic rhinitis (AR), atopic dermatitis (AD) and allergic asthma and improved treatment options are needed particularly for severe, refractory disease. Allergic diseases are complex and development involves both environmental and genetic factors. Although the existence of a genetic component for allergy was first described almost 100 years ago, progress in gene identification has been hindered by lack of high throughput technologies to investigate genetic variation in large numbers of subjects. The development of Genome-Wide Association Studies (GWAS), a hypothesis-free method of interrogating large numbers of common variants spanning the entire genome in disease and non-disease subjects has revolutionised our understanding of the genetics of allergic disease. Susceptibility genes for asthma, AR and AD have now been identified with confidence, suggesting there are common and distinct genetic loci associated with these diseases, providing novel insights into potential disease pathways and mechanisms. Genes involved in both adaptive and innate immune mechanisms have been identified, notably including multiple genes involved in epithelial function/secretion, suggesting that the airway epithelium may be particularly important in asthma. Interestingly, concordance/discordance between the genetic factors driving allergic traits such as IgE levels and disease states such as asthma have further supported the accumulating evidence for heterogeneity in these diseases. While GWAS have been useful and continue to identify novel genes for allergic diseases through increased sample sizes and phenotype refinement, future approaches will integrate analyses of rare variants, epigenetic mechanisms and eQTL approaches, leading to greater insight into the genetic basis of these diseases. Gene identification will improve our understanding of disease mechanisms and generate potential therapeutic opportunities.
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