Selection of genes for gene-environment interaction studies: a candidate pathway-based strategy using asthma as an example

Identifying a developmental transition in honey bees using gene expression data

In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.

Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions

A growing knowledge base of genetic and environmental information has greatly enabled the study of disease risk factors. However, the computational complexity and statistical burden of testing all variants by all environments has required novel study designs and hypothesis-driven approaches. We discuss how incorporating biological knowledge from model organisms, functional genomics, and integrative approaches can empower the discovery of novel gene-environment interactions and discuss specific methodological considerations with each approach. We consider specific examples where the application of these approaches has uncovered effects of gene-environment interactions relevant to drug response and immunity, and we highlight how such improvements enable a greater understanding of the pathogenesis of disease and the realization of precision medicine.

A pathway-based association study reveals variants from Wnt signalling genes contributing to asthma susceptibility

BACKGROUND

Genetic susceptibility to asthma is currently linked to a handful of genes which have a limited ability to predict the overall disease risk, suggesting the existence of many other genes involved in disease development. Accumulated evidence from association studies in genes related by biological pathways could reveal novel asthma genes.

OBJECTIVE

To reveal novel asthma susceptibility genes by means of a pathway-based association study.

METHODS

Based on summary data from a previous a genomewide association study (GWAS) of asthma, we first identified significant biological pathways using a gene-set enrichment analysis. We then mapped all tested single nucleotide polymorphisms (SNPs) on the genes contributing to significant pathways and prioritized those with a disproportionate number of nominal significant associations for further studies. For those prioritized genes, association studies were performed for selected SNPs in independent case-control samples (n = 1765) using logistic regression models, and results were meta-analysed with those from the GWAS.

RESULTS

Two biological processes were significantly enriched: the cytokine-cytokine receptor interaction (P = 0.002) and the Wnt signalling (P = 0.012). From the 417 genes interacting in these two pathways, 10 showed an excess of nominal associations, including a known asthma susceptibility locus (encoding SMAD family member 3) and other novel candidate genes. From the latter, association studies of 14 selected SNPs evidenced replication in a locus near the frizzled class receptor 6 (FZD6) gene (P = 9.90 × 10^-4 ), which had a consistent direction of effects with the GWAS findings (meta-analysed odds ratio = 1.49; P = 5.87 × 10^-6 ) and was in high linkage disequilibrium with expression quantitative trait loci in lung tissues.

CONCLUSIONS AND CLINICAL RELEVANCE

This study revealed the importance of two biological pathways in asthma pathogenesis and identified a novel susceptibility locus near Wnt signalling genes.

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

BACKGROUND

The biological mechanisms by which cleaning products and disinfectants-an emerging risk factor-affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma.

OBJECTIVES

We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma.

METHODS

Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway-based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons.

RESULTS

Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking.

CONCLUSIONS

Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207-214; http://dx.doi.org/10.1289/EHP376.

Susceptibility Factors Relevant for the Association Between Long-Term Air Pollution Exposure and Incident Asthma

In this review, we identified 15 studies in children and 10 studies in adults that assessed the association between long-term exposure to air pollution and incident asthma and that conducted stratified analyses to explore potential susceptibility factors. Overall, adult never-/former smokers seem to be at higher risk of incident asthma due to air pollution. Children without atopy and children from low socioeconomic status families also seem to be at higher risk of incident asthma due to air pollution. While interaction between air pollution and genes involved in the response to oxidative stress pathways have been explored, results are somewhat inconsistent and in need of replication. To evaluate interactions, large sample sizes are necessary, and much more research, including data pooling from existing studies, is needed to further explore susceptibility factors for asthma incidence due to long-term air pollution exposure.

Optimal Trend Tests for Genetic Association Studies of Heterogeneous Diseases

The Cochran-Armitage trend test is a standard procedure in genetic association studies. It is a directed test with high power to detect genetic effects that follow the gene-dosage model. In this paper, the author proposes optimal trend tests for genetic association studies of heterogeneous diseases. Monte-Carlo simulations show that the power gain of the optimal trend tests over the conventional Cochran-Armitage trend test is striking when the genetic effects are heterogeneous. The easy-to-use R 3.1.2 software (R Foundation for Statistical Computing, Vienna, Austria) code is provided. The optimal trend tests are recommended for routine use.

False Appearance of Gene-Environment Interactions in Genetic Association Studies

Under the assumption of gene-environment independence, unknown/unmeasured environmental factors, irrespective of what they may be, cannot confound the genetic effects. This may lead many people to believe that genetic heterogeneity across different levels of the studied environmental exposure should only mean gene-environment interaction--even though other environmental factors are not adjusted for. However, this is not true if the odds ratio is the effect measure used for quantifying genetic effects. This is because the odds ratio is a "noncollapsible" measure--a marginal odds ratio is not a weighted average of the conditional odds ratios, but instead has a tendency toward the null. In this study, the authors derive formulae for gene-environment interaction bias due to noncollapsibility. They use computer simulation and real data example to show that the bias can be substantial for common diseases. For genetic association study of nonrare diseases, researchers are advised to use collapsible measures, such as risk ratio or peril ratio.

Gene-environment interactions in the study of asthma in the postgenomewide association studies era

PURPOSE OF REVIEW

Asthma is a complex disease characterized by an intricate interplay of both heritable and environmental factors. Understanding the mechanisms through which genes and environment interact represents one of the major challenges for pulmonary researchers. This review provides an overview of the recently published literature on gene-environment (G × E) interactions in asthma, with a special focus on the new methodological developments in the postgenomewide association studies (GWAS) era.

RECENT FINDINGS

Most recent studies on G × E interaction in asthma used a candidate-gene approach. Candidate-gene studies considering exposure to outdoor air pollutants showed significant interactions mainly with variants in the GSTP1 gene on asthma in children. G × E studies on passive and active smoking, including one genomewide interaction study, identified novel genes of susceptibility to asthma and a time-dependent effect of maternal smoking. Other recent studies on asthma found interactions between candidate genes and occupational allergen exposure and several domestic exposures such as endotoxin and gas cooking. New methods were developed to efficiently estimate G × E interaction in GWAS, and a pathway-based strategy to select an enriched gene-set for G × E studies has recently been proposed.

SUMMARY

The G × E studies presented in this review offer a good example on how candidate-gene approaches can complement and help in validating GWAS findings.

[Genetic and environmental factors of asthma and allergy: Results of the EGEA study]

INTRODUCTION AND METHODS

The EGEA study (epidemiological study on the genetics and environment of asthma, bronchial hyperresponsiveness and atopy), which combines a case-control and a family-based study of asthma case (n=2120 subjects) with three surveys over 20 years, aims to identify environmental and genetic factors associated with asthma and asthma-related phenotypes. We summarize the results of the phenotypic characterization and the investigation of environmental and genetic factors of asthma and asthma-related phenotypes obtained since 2007 in the EGEA study (42 articles).

RESULTS

Both epidemiological and genetic results confirm the heterogeneity of asthma. These results strengthen the role of the age of disease onset, the allergic status and the level of disease activity in the identification of the different phenotypes of asthma. The deleterious role of active smoking, exposure to air pollution, occupational asthmogenic agents and cleaning products on the prevalence and/or activity of asthma has been confirmed. Accounting for gene-environment interactions allowed the identification of new genetic factors underlying asthma and asthma-related traits and better understanding of their mode of action.

CONCLUSION

The EGEA study is contributing to the advances in respiratory research at the international level. The new phenotypic, environmental and biological data available in EGEA study will help characterizing the long-term evolution of asthma and the factors associated to this evolution.

Have recent investigations into remission from childhood asthma helped in understanding the pathogenesis of this disease?

Studies show that a significant proportion of young people suffering from childhood onset asthma later recovered, usually in adolescence. In this article we argue that an understanding of the differences between children who recover from asthma and those who do not would contribute to increased understanding of the pathogenic mechanisms of the disease and could provide new clues about prevention and treatment. We note that some researchers have recently published results from these kinds of investigations. This paper reports results regarding genetic determinants, distorted mechanisms of inflammation, and mind/body relationships. We also try to integrate findings from these 3 areas to formulate general conclusions about the pathogenesis of asthma.