共 92 条
Gene-environment interactions in childhood asthma revisited; expanding the interaction concept
被引:35
作者:

Hernandez-Pacheco, Natalia
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机构:
Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden
CIBER Enfermedades Respiratorias CIBERES, Madrid, Spain Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden

Kere, Maura
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机构:
Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden

Melen, Erik
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h-index: 0
机构:
Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden
South Gen Hosp, Sachs Childrens Hosp, Stockholm, Sweden Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden
机构:
[1] Karolinska Inst, Dept Clin Sci & Educ, Sodersjukhuset, Sjukhusbacken 10, SE-11883 Stockholm, Sweden
[2] CIBER Enfermedades Respiratorias CIBERES, Madrid, Spain
[3] South Gen Hosp, Sachs Childrens Hosp, Stockholm, Sweden
基金:
瑞典研究理事会;
关键词:
asthma;
children;
environmental exposure;
epigenetics;
genetics;
genome-wide interaction study;
methylation;
omics;
AIR-POLLUTION;
MATERNAL SMOKING;
DNA METHYLATION;
LUNG-FUNCTION;
RISK;
EXPOSURE;
CHILDREN;
VARIANTS;
EXPRESSION;
EPIGENOME;
D O I:
10.1111/pai.13780
中图分类号:
R392 [医学免疫学];
学科分类号:
100102 ;
摘要:
Investigation of gene-environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome-wide approaches. The best example to date is the major asthma locus on the 17q12-21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant-single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.
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