Cargando…
Genomic Predictors of Asthma Phenotypes and Treatment Response
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, ran...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370703/ https://www.ncbi.nlm.nih.gov/pubmed/30805318 http://dx.doi.org/10.3389/fped.2019.00006 |
_version_ | 1783394403003400192 |
---|---|
author | Hernandez-Pacheco, Natalia Pino-Yanes, Maria Flores, Carlos |
author_facet | Hernandez-Pacheco, Natalia Pino-Yanes, Maria Flores, Carlos |
author_sort | Hernandez-Pacheco, Natalia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6370703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63707032019-02-25 Genomic Predictors of Asthma Phenotypes and Treatment Response Hernandez-Pacheco, Natalia Pino-Yanes, Maria Flores, Carlos Front Pediatr Pediatrics 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. Frontiers Media S.A. 2019-02-05 /pmc/articles/PMC6370703/ /pubmed/30805318 http://dx.doi.org/10.3389/fped.2019.00006 Text en Copyright © 2019 Hernandez-Pacheco, Pino-Yanes and Flores. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pediatrics Hernandez-Pacheco, Natalia Pino-Yanes, Maria Flores, Carlos Genomic Predictors of Asthma Phenotypes and Treatment Response |
title | Genomic Predictors of Asthma Phenotypes and Treatment Response |
title_full | Genomic Predictors of Asthma Phenotypes and Treatment Response |
title_fullStr | Genomic Predictors of Asthma Phenotypes and Treatment Response |
title_full_unstemmed | Genomic Predictors of Asthma Phenotypes and Treatment Response |
title_short | Genomic Predictors of Asthma Phenotypes and Treatment Response |
title_sort | genomic predictors of asthma phenotypes and treatment response |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370703/ https://www.ncbi.nlm.nih.gov/pubmed/30805318 http://dx.doi.org/10.3389/fped.2019.00006 |
work_keys_str_mv | AT hernandezpacheconatalia genomicpredictorsofasthmaphenotypesandtreatmentresponse AT pinoyanesmaria genomicpredictorsofasthmaphenotypesandtreatmentresponse AT florescarlos genomicpredictorsofasthmaphenotypesandtreatmentresponse |