GxE Effects Research Articles

Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank

Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum.We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders.We included 33 k–380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3–5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01–0.02% variance explained to the corresponding additive model.PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.

Mitigating type 1 error inflation and power loss in GxE PRS: Genotype-environment interaction in polygenic risk score models.

The use of polygenic risk score (PRS) models has transformed the field of genetics by enabling the prediction of complex traits and diseases based on an individual's genetic profile. However, the impact of genotype-environment interaction (GxE) on the performance and applicability of PRS models remains a crucial aspect to be explored. Currently, existing genotype-environment interaction polygenic risk score (GxE PRS) models are often inappropriately used, which can result in inflated type 1 error rates and compromised results. In this study, we propose novel GxE PRS models that jointly incorporate additive and interaction genetic effects although also including an additional quadratic term for nongenetic covariates, enhancing their robustness against model misspecification. Through extensive simulations, we demonstrate that our proposed models outperform existing models in terms of controlling type 1 error rates and enhancing statistical power. Furthermore, we apply the proposed models to real data, and report significant GxE effects. Specifically, we highlight the impact of our models on both quantitative and binary traits. For quantitative traits, we uncover the GxE modulation of genetic effects on body mass index by alcohol intake frequency. In the case of binary traits, we identify the GxE modulation of genetic effects on hypertension by waist-to-hip ratio. These findings underscore the importance of employing a robust model that effectively controls type 1 error rates, thus preventing the occurrence of spurious GxE signals. To facilitate the implementation of our approach, we have developed an innovative R software package called GxEprs, specifically designed to detect and estimate GxE effects. Overall, our study highlights the importance of accurate GxE modeling and its implications for genetic risk prediction, although providing a practical tool to support further research in this area.

GxE interaction effects of HCRTR2 single nucleotide polymorphism and adverse childhood experiences on methamphetamine use disorder

ABSTRACT Background: Methamphetamine use disorder (MUD) is a worldwide health concern. The hypothalamic orexin system regulates stress response and addictive behaviors. The genetic variation in the hypocretin receptor 2 (HCRTR2), rs2653349, is associated with substance use disorder. Objectives: We explored the gene-environment (GxE) interaction of rs2653349 and adverse childhood experiences (ACEs) associated with MUD susceptibility. Methods: Four hundred and one individuals (336 males, 65 females) with MUD and 348 healthy controls (288 males, 60 females) completed a self-report questionnaire evaluating ACEs, encompassing childhood abuse and household dysfunction categories, and were genotyped for SNP rs2653349. Methamphetamine use variables were collected using the Diagnostic Interview for Genetic Studies. We used regression analyses to assess the GxE effect on MUD risk. Results: The MUD group had a comparable genotypic distribution for rs2653349 to the control group, albeit with a higher prevalence and number of types of ACEs, correlating with an increased MUD risk (p < .05). No significant genetic impact of rs2653349 on MUD risk was found. However, we observed a GxE interaction effect between the minor allele of rs2653349 and the number of childhood abuse or household dysfunction types, correlating with a reduced MUD risk (OR = -0.71, p = .04, Benjamini-Hochberg adjusted p = .08 and OR = -0.59, p = .045, Benjamini-Hochberg adjusted p = .09, respectively). Conclusion: HCRTR2 SNP rs2653349 has no significant impact on MUD risk, but ACEs may increase this risk. GxE results suggest that rs2653349 could offer protection against developing MUD in individuals experiencing multiple types of ACEs.

Genetic parameters for milk production and type traits in North American and European Alpine and Saanen dairy goat populations

The development of an across-country genomic evaluation scheme is a promising alternative for enlarging reference populations and successfully implementing genomic selection in small ruminant populations. However, the feasibility of such evaluations depends on the genetic similarity among the populations, and therefore, high connectedness and high genetic correlations between the traits recorded in different countries or populations are needed. In this study, we evaluated the feasibility of performing an across-country genomic evaluation for milk production and type traits in Alpine and Saanen goats from Canada, France, Italy, and Switzerland. Variance components and genetic parameters, including genetic correlations between traits recorded in different countries, were calculated using combined phenotypes, genotypes, and pedigree datasets. The (co)variance component analyses were performed within breed, either based only on pedigree information or also incorporating genomic information. Across-country genetic parameters were calculated for 3 representative traits (i.e., milk yield, fat content, and rear udder attachment). The heritability estimates ranged from 0.10 to 0.50, which are consistent with previous estimates reported in the literature. The genetic correlations for rear udder attachment ranged from 0.75 (between France and Italy, for the Alpine breed without genomic information) to 0.95 (between Canada and France, for the Saanen breed with genomic information), whereas for fat content, between France and Italy, they ranged from 0.75 in the Alpine breed without genomic information to 0.78 in the Alpine breed with genomic information. However, genetic correlations for milk yield were only estimable between France and Italy, with a moderate value of 0.45 for the Alpine breed with or without genomic information, and of 0.22 and 0.26 in the Saanen breed with and without genomic information, respectively. These low genetic correlations for milk yield could be due to several factors, including the trait definition in each country and genotype-by-environment interactions (GxE). The high genetic correlations found for fat content and rear udder attachment indicate that these traits might be more standardized across countries and less affected by GxE effects. Thus, an international genomic evaluation for these traits might be feasible. Further studies should be performed to understand the surprisingly lower genetic correlations between milk yield across countries. Furthermore, additional efforts should be made to increase the genetic connection among the Alpine and Saanen goat populations in the 4 countries included in the analyses.

Association of polygenic scores for depression and neuroticism with perceived stress in daily life during a long-lasting stress period.

Genetic factors contribute significantly to interindividual differences in the susceptibility to stress-related disorders. As stress can also be conceptualized as environmental exposure, controlled gene-environment interaction (GxE) studies with an in-depth phenotyping may help to unravel mechanisms underlying the interplay between genetic factors and stress. In a prospective-longitudinal quasi-experimental study, we investigated whether polygenic scores (PGS) for depression (DEP-PGS) and neuroticism (NEU-PGS), respectively, were associated with responses to chronic stress in daily life. We examined law students (n = 432) over 13 months. Participants in the stress group experienced a long-lasting stress phase, namely the preparation for the first state examination for law students. The control group consisted of law students without particular stress exposure. In the present manuscript, we analyzed perceived stress levels assessed at high frequency and in an ecologically valid manner by ambulatory assessments as well as depression symptoms and two parameters of the cortisol awakening response. The latter was only assessed in a subsample (n = 196). No associations between the DEP-PGS and stress-related variables were found. However, for the NEU-PGS we found a significant GxE effect. Only in individuals experiencing academic stress a higher PGS for neuroticism predicted stronger increases of perceived stress levels until the exam. At baseline, a higher NEU-PGS was associated with higher perceived stress levels in both groups. Despite the small sample size, we provide preliminary evidence that the genetic disposition for neuroticism is associated with stress level increases in daily life during a long-lasting stress period.

Evolutionary consequences of microbiomes for hosts: impacts on host fitness, traits, and heritability.

An organism's phenotypes and fitness often depend on the interactive effects of its genome (Gh⁢o⁢s⁢t), microbiome (Gm⁢i⁢c⁢r⁢o⁢b⁢e), and environment (E). These G × G, G × E, and G × G × E effects fundamentally shape host-microbiome (co)evolution and may be widespread, but are rarely compared within a single experiment. We collected and cultured L⁢e⁢m⁢n⁢am⁢i⁢n⁢o⁢r (duckweed) and its associated microbiome from 10 sites across an urban-to-rural ecotone. We factorially manipulated host genotype and microbiome in two environments (low and high zinc, an urban aquatic stressor) in an experiment with 200 treatments: 10 host genotypes × 10 microbiomes × 2 environments. Host genotype explained the most variation in L.m⁢i⁢n⁢o⁢r fitness and traits, while microbiome effects often depended on host genotype (G × G). Microbiome composition predicted G × G effects: when compared in more similar microbiomes, duckweed genotypes had more similar effects on traits. Further, host fitness increased and microbes grew faster when applied microbiomes more closely matched the host's field microbiome, suggesting some local adaptation between hosts and microbiota. Finally, selection on and heritability of host traits shifted across microbiomes and zinc exposure. Thus, we found that microbiomes impact host fitness, trait expression, and heritability, with implications for host-microbiome evolution and microbiome breeding.

Uncovering genetic parameters and environmental influences on fertility, milk production, and quality in autochthonous Reggiana cattle

Reggiana is a local cattle breed from northern Italy known for its rusticity and profitability, due to the production of branded Parmigiano Reggiano cheese. To ensure the persistence of such profitability in the long term, an adequate breeding program is required. To this aim, in the present study we estimate the genetic parameters of the main productive and reproductive traits, and we evaluate the effect of genotype by environment interaction (GxE) on these traits using 2 environmental covariates: (1) productivity and (2) temperature-humidity index (THI). Milk, fat, protein, and casein yield were considered as daily production traits, whereas protein, fat, casein percentage, casein index, and somatic cell score were considered as milk quality traits. Finally, reproductive traits such as the number of inseminations, days open, calving interval, and calving-to-first-insemination interval were evaluated. Reggiana cattle produce an average of 19 kg of milk per day with 3.7% fat and 3.4% protein content and have excellent fertility parameters. Compared with other breeds, they have slightly lower heritability for production and quality for production traits (e.g., 0.12 [0.09; 0.15] for milk yield), but similar heritability for fertility traits. Milk, protein, and fat daily yields are highly correlated but negatively correlated with the percentage of protein, fat, and casein, whereas fertility traits have an unfavorable genetic correlation with daily production traits. When considering productivity, a consistent amount of variability due to GxE was observed for all daily production traits, somatic cell count, and casein index. A modest amount of GxE was observed for fertility parameters, while the percentage of solid content showed almost no GxE effect. A similar situation occurred when considering the THI, but no GxE interaction was observed for reproduction traits. In conclusion, this study provides useful information for the implementation of accurate selection plans in this local breed, accounting for environmental plasticity measured through the consistent GxE interaction observed.

Systematic review on gene-sun exposure interactions in skin cancer.

The risk of skin cancer is determined by environmental factors like ultraviolet radiation (UVR), personal habits like time spent outdoors and genetic factors. This review aimed to survey existing studies in gene-environment (GxE) interaction on skin cancer risk, and report on GxE effect estimates. We searched Embase, Medline (Ovid) and Web of Science (Core Collection) and included only primary research that reported on GxE on the risk of the three most common types of skin cancer: basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and melanoma. Quality assessment followed the Newcastle-Ottawa Scale. Meta-analysis was not possible because no two studies examined the same interaction. This review was registered on PROSPERO (CRD42021238064). In total 260 records were identified after exclusion of duplicates. Fifteen studies were included in the final synthesis-12 used candidate gene approach. We found some evidence of GxE interactions with sun exposure, notably, with MC1R, CAT and NOS1 genes in melanoma, HAL and IL23A in BCC and HAL and XRCC1 in SCC. Sun exposure seems to interact with genes involved in pigmentation, oxidative stress and immunosuppression, indicating that excessive UV exposure might exhaust oxidative defence and repair systems differentially, dependent on genetic make-up. Further research is warranted to better understand skin cancer epidemiology and develop sun exposure recommendations. A genome-wide approach is recommended as it might uncover unknown disease pathways dependent on UV radiation.

Relationships between phenotypic plasticity and epigenetic variation in two Caribbean Acropora corals.

The plastic ability for a range of phenotypes to be exhibited by the same genotype allows organisms to respond to environmental variation and may modulate fitness in novel environments. Differing capacities for phenotypic plasticity within a population, apparent as genotype by environment interactions (GxE), can therefore have both ecological and evolutionary implications. Epigenetic gene regulation alters gene function in response to environmental cues without changes to the underlying genetic sequence and likely mediates phenotypic variation. DNA methylation is currently the most well described epigenetic mechanism and is related to transcriptional homeostasis in invertebrates. However, evidence quantitatively linking variation in DNA methylation with that of phenotype is lacking in some taxa, including reef-building corals. In this study, spatial and seasonal environmental variation in Bonaire, Caribbean Netherlands was utilized to assess relationships between physiology and DNA methylation profiles within genetic clones across different genotypes of Acropora cervicornis and A. palmata corals. The physiology of both species was highly influenced by environmental variation compared to the effect of genotype. GxE effects on phenotype were only apparent in A. cervicornis. DNA methylation in both species differed between genotypes and seasons and epigenetic variation was significantly related to coral physiological metrics. Furthermore, plastic shifts in physiology across seasons were significantly positively correlated with shifts in DNA methylation profiles in both species. These results highlight the dynamic influence of environmental conditions and genetic constraints on the physiology of two important Caribbean coral species. Additionally, this study provides quantitative support for the role of epigenetic DNA methylation in mediating phenotypic plasticity in invertebrates.

Gene-environment interactions and the case of body mass index and obesity: How much do they matter?

We investigate the demographic and population health implications of gene-environment interactions (GxE) in the case of body mass index (BMI) and obesity. We seek to answer two questions: (a) what is the first-order impact of GxE effects on BMI and probability of obesity, e.g. the direct causal effect of G in different E's? and (b) how large is the impact of GxE effects on second-order health outcomes associated with BMI and obesity, such as type 2 diabetes (T2D) and disability? In contrast to most of the literature that focuses on estimating GxE effects, we study the implications of GxE effects for population health outcomes that are downstream of a causal chain that includes the target phenotype (in this case BMI) as the initial cause. To limit the scope of the paper, we focus on environments defined by birth cohorts. However, extensions to other environments (education, socioeconomic status (SES), early conditions, and physical settings) are straightforward.

Inducible and Conditional Activation of Adult Neurogenesis Rescues Cadmium-Induced Hippocampus-Dependent Memory Deficits in ApoE4-KI Mice.

The apolipoprotein E (ApoE) gene is a genetic risk factor for late-onset Alzheimer's disease, in which ε4 allele carriers have increased risk compared to the common ε3 carriers. Cadmium (Cd) is a toxic heavy metal and a potential neurotoxicant. We previously reported a gene-environment interaction (GxE) effect between ApoE4 and Cd that accelerates or increases the severity of the cognitive decline in ApoE4-knockin (ApoE4-KI) mice exposed to 0.6 mg/L CdCl2 through drinking water compared to control ApoE3-KI mice. However, the mechanisms underlying this GxE effect are not yet defined. Because Cd impairs adult neurogenesis, we investigated whether genetic and conditional stimulation of adult neurogenesis can functionally rescue Cd-induced cognitive impairment in ApoE4-KI mice. We crossed either ApoE4-KI or ApoE3-KI to an inducible Cre mouse strain, Nestin-CreERTM:caMEK5-eGFPloxP/loxP (designated as caMEK5), to generate ApoE4-KI:caMEK5 and ApoE3-KI:caMEK5. Tamoxifen administration in these mice genetically and conditionally induces the expression of caMEK5 in adult neural stem/progenitor cells, enabling the stimulation of adult neurogenesis in the brain. Male ApoE4-KI:caMEK5 and ApoE3-KI:caMEK5 mice were exposed to 0.6 mg/L CdCl2 throughout the experiment, and tamoxifen was administered once Cd-induced impairment in spatial working memory was consistently observed. Cd exposure impaired spatial working memory earlier in ApoE4-KI:caMEK5 than in ApoE3-KI:caMEK5 mice. In both strains, these deficits were rescued after tamoxifen treatment. Consistent with these behavioral findings, tamoxifen treatment enhanced adult neurogenesis by increasing the morphological complexity of adult-born immature neurons. These results provide evidence for a direct link between impaired spatial memory and adult neurogenesis in this GxE model.

Gene-environment interplay in early life cognitive development

Children's differences in early life cognitive development are driven by the interplay of genetic and environmental factors, but identifying replicable gene-environment interactions (GxE) has proven difficult. We systematically tested GxE effects in the prediction of cognitive development from 2 to 4 years, using polygenic scores (PGS) for years spent in education and 39 measures of the home and neighborhood environment. Data came from up to 6973 unrelated individuals from the Twins Early Development Study (TEDS), a UK population-representative cohort. The environmental measures accounted together for 20.6% of the variance in cognitive development, while the PGS accounted for 0.5% (p < .001). We observed substantial gene-environment correlations but found no conclusive evidence for GxE effects. While associations between PGS and cognitive development were weak, genetic and environmental factors had direct and additive (i.e., main effects) rather than interactive influences on early life cognitive development.

Bias in Gene-by-Environment Interaction Effects with Sum Scores; An Application to Well-being Phenotypes

In the current study, we investigated the influence of using skewed sum scores on estimated gene-by-environment interaction effects (GxE) for life satisfaction and happiness with perceived social support. To this end, we analyzed item-level data from a large adult twin sample (Ns between 3610 and 11,305) of the Netherlands Twin Register. Item response theory (IRT) models were incorporated in unmeasured (univariate) GxE models, and measured GxE models (with social support as moderator). We found that skewness introduced spurious GxE effects, with the largest effect for the most skewed variable (social support). Finally, in the IRT model for life satisfaction, but not for happiness, heritability estimates decreased with higher social support, while this was not observed when analyzing sum scores. Together, our results indicate that IRT can be used to address psychometric issues related to the use of sum scores, especially in the context of GxE, for complex traits like well-being.

A Varying Coefficient Model to Jointly Test Genetic and Gene-Environment Interaction Effects.

Most human traits are influenced by the interplay between genetic and environmental factors. Many statistical methods have been proposed to screen for gene-environment interaction (GxE) in the post genome-wide association study era. However, most of the existing methods assume a linear interaction between genetic and environmental factors toward phenotypic variations, which diminishes statistical power in the case of nonlinear GxE. In this paper, we present a flexible statistical procedure to detect GxE regardless of whether the underlying relationship is linear or not. By modeling the joint genetic and GxE effects as a varying-coefficient function of the environmental factor, the proposed model is able to capture dynamic trajectories of GxE. We employ a likelihood ratio test with a fast Monte Carlo algorithm for hypothesis testing. Simulations were conducted to evaluate validity and power of the proposed model in various settings. Real data analysis was performed to illustrate its power, in particular, in the case of nonlinear GxE.

Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure.

Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical's potential to elicit GxE is often not considered during risk assessment. Previously, we've leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE.

Mega-environment analysis to assess adaptability, stability, and genomic predictions in grain sorghum hybrids

Multi-environment trials (MET) are fundamental for assessing genotype-by-environment interaction (GxE) effects, adaptability and stability of genotypes and provide valuable information about target regions. As such, a MET involving grain sorghum hybrid combinations derived from elite inbred lines adapted to diverse sorghum production regions was developed to assess agronomic performance, stability, and genomic-enabled prediction accuracies within mega-environments (ME). Ten females and ten males from the Texas A&M and Kansas State sorghum breeding programs were crossed following a factorial mating scheme to generate 100 hybrids. Grain yield, plant height, and days to anthesis were assessed in a MET consisting of ten environments across Texas and Kansas over two years. Genotype plus Genotype-by-block-of-environment biplot (GGB) assessed ME, while the "mean-vs-stability" view of the biplot and the Bayesian Finlay–Wilkinson regression evaluated hybrid adaptability and stability. A genomic prediction model including the GxE effect was applied within ME to assess prediction accuracy. Results suggest that grain sorghum hybrid combinations involving lines adapted to different target regions can produce superior hybrids. GGB confirmed distinct regions of sorghum adaption in the U.S. Further, genomic predictions within ME reported inconsistent results, suggesting that additional effects rather than the correlations between environments are influencing genomic prediction of grain sorghum hybrids.

Gene-Environment Interactions in Vitamin D Status and Sun Exposure: A Systematic Review with Recommendations for Future Research.

Vitamin D is essential for good health. Dermal vitamin D production is dependent on environmental factors such as season and latitude, and personal factors such as time spent outdoors and genetics. Varying heritability of vitamin D status by season has been reported, suggesting that gene-environment interactions (GxE) may play a key role. Thus, understanding GxE might significantly improve our understanding of determinants of vitamin D status. The objective of this review was to survey the existing methods in GxE on vitamin D studies and report on GxE effect estimates. We searched the Embase, Medline (Ovid), and Web of Science (Core Collection) databases. We included only primary research that reported on GxE effects on vitamin D status using 25-hydroxyvitamin D as a biomarker. Sun exposure was the only environmental exposure identified in these studies. The quality assessment followed the Newcastle–Ottawa Scale for cohort studies. Seven studies were included in the final narrative synthesis. We evaluate the limitations and findings of the available GxE in vitamin D research and provide recommendations for future GxE research. The systematic review was registered on PROSPERO (CRD42021238081).

Airway inflammation in adolescents and elderly women: Chronic air pollution exposure and polygenic susceptibility

Background and aimThe fractional exhaled nitric oxide (FeNO) concentration in the exhaled breath is a biomarker for eosinophilic airway inflammation. We explored the interplay between chronic air pollution exposure and polygenic susceptibility to airway inflammation at different critical age stages. MethodsAdolescents (15 yr) enrolled in the GINIplus/LISA birth cohorts (n = 2434) and 220 elderly women (75 yr on average) enrolled in the SALIA cohort with FeNO measurements available were investigated. Environmental main effects of the mean of ESCAPE land-use regression air pollutant concentrations within a time window of 15 years and main effects of the polygenic risk scores (PRS) using internal weights from elastic net regression of genome-wide derived single nucleotide polymorphisms were investigated. Furthermore, we examined gene-environment interaction (GxE) effects on natural log-transformed FeNO levels by adjusted linear regression models. ResultsWhile we observed no significant environmental and polygenic main effects on airway inflammation in either age group, we found robust harmful effects of chronic nitrogen dioxide (NO2) exposure in the GxE models for elderly women (16.2 % increase in FeNO, p-value = 0.027). Stratified analyses found GxE effects between the PRS and chronic NO2 exposure in never-smoker elderly women and in adolescents without any inflammatory respiratory conditions. ConclusionsFeNO measurement is a useful biomarker to detect higher risk of NO2-induced eosinophilic airway inflammation in the elderly. There was limited evidence for GxE effects on airway inflammation in adolescents or the elderly. Further GxE studies in subpopulations should be conducted to investigate the assumption that susceptibility to airway inflammation differs between age stages.

Gene-environment interactions in childhood asthma revisited; expanding the interaction concept.

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.

Early adversity as the prototype gene × environment interaction in mental disorders?

Childhood adversity (CA) as a significant stressor has consistently been associated with the development of mental disorders. The interaction between CA and genetic variants has been proposed to play a substantial role in disease etiology.In this review, we focus on the gene by environment (GxE) paradigm, its background and interpretation and stress the necessity of its implementation in psychiatric research. Further, we discuss the findings supporting GxCA interactions, ranging from candidate gene studies to polygenic and genome-wide approaches, their strengths and limitations. To illustrate potential underlying epigenetic mechanisms by which GxE effects are translated, we focus on results from FKBP5 × CA studies and discuss how molecular evidence can supplement previous GxE findings.In conclusion, while GxE studies constitute a valuable line of investigation, more harmonized GxE studies in large, deep-phenotyped, longitudinal cohorts, and across different developmental stages are necessary to further substantiate and understand reported GxE findings.