Gene-environment interactions in asthma and allergic diseases: challenges and perspectives.

J Allergy Clin Immunol

INSERM, CESP Centre for research in Epidemiology and Population Health, U1018, Respiratory and Environmental Epidemiology Team, Villejuif, France.

Published: December 2012

The concept of gene-environment (GxE) interactions has dramatically evolved in the last century and has now become a central theme in studies that assess the causes of human disease. Despite the numerous efforts to discover genes associated in asthma and allergy through various approaches, including the recent genome-wide association studies, investigation of GxE interactions has been mainly limited to candidate genes, candidate environmental exposures, or both. This review discusses the various strategies from hypothesis-driven strategies to the full agnostic search of GxE interactions with an illustration from recently published articles. Challenges raised by each piece of the puzzle (ie, phenotype, environment, gene, and analysis of GxE interaction) are put forward, and tentative solutions are proposed. New perspectives to integrate various types of data generated by new sequencing technologies and to progress toward a systems biology approach of disease are outlined. The future of a molecular network-based approach of disease to which GxE interactions are related requires space for innovative and multidisciplinary research. Assembling the various parts of a puzzle in a complex system could well occur in a way that might not necessarily follow the rules of logic.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jaci.2012.10.038DOI Listing

Publication Analysis

Top Keywords

gxe interactions
16
approach disease
8
gxe
5
gene-environment interactions
4
interactions asthma
4
asthma allergic
4
allergic diseases
4
diseases challenges
4
challenges perspectives
4
perspectives concept
4

Similar Publications

Maternal exposures are known to influence the risk of isolated cleft lip with or without cleft palate (CL/P) - a common and highly heritable birth defect with a multifactorial etiology. To identify new CL/P risk loci, we conducted a genome-wide gene-environment interaction (GEI) analysis of CL/P on a sample of 540 cases and 260 controls recruited from the Philippines, incorporating the interaction effects of genetic variants with maternal smoking and vitamin use. As GEI analyses are typically low in power and the results can be difficult to interpret, we used multiple testing frameworks to evaluate potential GEI effects: 1 degree-of-freedom (1df) GxE test, the 3df joint test, and the two-step EDGE approach.

View Article and Find Full Text PDF

Identifying the genetic basis of local adaptation is a key goal in evolutionary biology. Allele frequency clines along environmental gradients, known as genotype-environment associations (GEA), are often used to detect potential loci causing local adaptation, but GEA are rarely followed by experimental validation. Here, we tested loci identified in three different moisture-related GEA studies on Arabidopsis.

View Article and Find Full Text PDF

Phenotypic plasticity can contribute to crop adaptation to challenging environments. Plasticity indices are potentially useful to identify the genetic basis of crop phenotypic plasticity. Numerous methods exist to measure phenotypic plasticity.

View Article and Find Full Text PDF

Background: Obesity is a global health issue influenced primarily by genetic variants and environmental factors. This study aimed to examine the relationship between genetic and lifestyle factors and their interaction with obesity risk among university students.

Methods: A total of 658 students from the same university participated in this study, including 531 females (mean age (SD): 21.

View Article and Find Full Text PDF

Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!