4.5 Review

Genomic Predictors of Asthma Phenotypes and Treatment Response

Journal

FRONTIERS IN PEDIATRICS
Volume 7, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fped.2019.00006

Keywords

admixture mapping; asthma; genomics; genome-wide association study; multiomics; personalized medicine

Categories

Funding

  1. Instituto de Salud Carlos III (ISCIII) - European Regional Development Funds, A way of making Europe from the European Union [PI17/00610]
  2. Strategic Action for Health Research (AES) [AC15/00015]
  3. European Community (EC) within the Active and Assisted Living (AAL) [AC15/00015]
  4. SysPharmPedia grant from the ERACoSysMed 1st Joint Transnational Call from the European Union under theHorizon 2020
  5. ISCIII [FI16/00136]
  6. European Social Funds from the European Union (ESF) ESF invests in your future
  7. Ramon y Cajal Program [RYC-2015-17205]
  8. Spanish Ministry of Economy, Industry and Competitiveness [SAF2017-83417R]
  9. Spanish Ministry of Science, Innovation and Universities [RTC-2017-6471-1]
  10. Instituto Tecnologico y de Energias Renovables (ITER) [OA17/008]

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Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.

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