About this Research Topic
The prevalence of allergy and asthma have been growing in recent years in industrialized countries. Multiple and, to a great extent, unknown interactions between genetic and environmental factors are surely beyond that fact. At the same time, the knowledge about the intrinsic mechanisms leading to the development of allergies and asthma has enormously increased throughout the last decades. Thus, a considerable body of evidence illustrating the importance of several “omics” in this respect (metabolomics, proteomics, microbiomics, epigenomics, transcriptomics…) is being constantly generated.
Then, the possibility to successfully intervene in early phases of the allergic disease or even before its beginning, seems not to be a chimera in the medium term. However, the complexity and variability in relation to multiple underlying pheno-endotypes in allergy and asthma, as well as the possibility that uncountable environmental factors can have a decisive role in this respect, adds an extreme difficulty to the issue. Nevertheless, the use of supervised and unsupervised machine-learning approaches based on pattern recognition computer algorithms could decisively contribute to unravel the complexity and variability in relation to multiple underlying pheno-endotypes in allergy and asthma.
This would provide a more robust foundation to newly growing paradigm based on the “personalized medicine”, since this strategy would permit more precise, safe and tailored preventative and therapeutic actions for each individual. This research topic welcomes submissions of all article types related to these primary preventative mechanisms in pediatric allergy and asthma.
Keywords: Asthma, Allergy, primary prevention, omics, personalised medicine
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