A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p<0.05/200) with a ratio of GxE to additive heritability of ≈6.8% on average. Analyzing ≈8 million imputed SNPs (MAF ≥0.1%), we documented an approximate 28% increase in genome-wide GxE heritability compared to array SNPs. We partitioned GxE heritability across minor allele frequency (MAF) and local linkage disequilibrium (LD) values, revealing that, like additive allelic effects, GxE allelic effects tend to increase with decreasing MAF and LD. Analyzing GxE heritability near genes highly expressed in specific tissues, we find significant brain-specific enrichment for body mass index (BMI) and basal metabolic rate in the context of smoking and adipose-specific enrichment for waist-hip ratio (WHR) in the context of sex.

Crosstalk of MAP3K1 and EGFR signaling mediates gene-environment interactions that block developmental tissue closure.

Aberrant regulation of signal transduction pathways can adversely derail biological processes for tissue development. One such process is the embryonic eyelid closure that is dependent on the mitogen-activated protein kinase kinase kinase 1 (MAP3K1). Map3k1 KO in mice results in defective eyelid closure and an autosomal recessive eye-open at birth phenotype. We have shown that in utero exposure to dioxin, a persistent environmental toxicant, induces the same eye defect in Map3k1+/- heterozygous but not WT pups. Here, we explore the mechanisms of the Map3k1 (gene) and dioxin (environment) interactions (GxE) underlying defective eyelid closure. We show that, acting through the aryl hydrocarbon receptor, dioxin activates epidermal growth factor receptor signaling, which in turn depresses MAP3K1-dependent Jun N-terminal kinase (JNK) activity. The dioxin-mediated JNK repression is moderate but is exacerbated by Map3k1 heterozygosity. Therefore, dioxin exposed Map3k1+/- embryonic eyelids have a marked reduction of JNK activity, accelerated differentiation and impeded polarization in the epithelial cells. Knocking out Ahr or Egfr in eyelid epithelium attenuates the open-eye defects in dioxin-treated Map3k1+/- pups, whereas knockout of Jnk1 and S1pr that encodes the sphigosin-1-phosphate (S1P) receptors upstream of the MAP3K1-JNK pathway potentiates the dioxin toxicity. Our novel findings show that the crosstalk of aryl hydrocarbon receptor, epidermal growth factor receptor, and S1P-MAP3K1-JNK pathways determines the outcome of dioxin exposure. Thus, gene mutations targeting these pathways are potential risk factors for the toxicity of environmental chemicals.

Leveraging phenotypic variability to identify genetic interactions in human phenotypes.

Although thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly because of the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to when assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

A polygenic-score-based approach for identification of gene-drug interactions stratifying breast cancer risk.

An individual's genetics can dramatically influence breast cancer (BC) risk. Although clinical measures for prevention do exist, non-invasive personalized measures for reducing BC risk are limited. Commonly used medications are a promising set of modifiable factors, but no previous study has explored whether a range of widely taken approved drugs modulate BC genetics. In this study, we describe a quantitative framework for exploring the interaction between the genetic susceptibility of BC and medication usage among UK Biobank women. We computed BC polygenic scores (PGSs) that summarize BC genetic risk and find that the PGS explains nearly three-times greater variation in disease risk within corticosteroid users compared to non-users. We map 35 genes significantly interacting with corticosteroid use (FDR < 0.1), highlighting the transcription factor NRF2 as a common regulator of gene-corticosteroid interactions in BC. Finally, we discover a regulatory variant strongly stratifying BC risk according to corticosteroid use. Within risk allele carriers, 18.2% of women taking corticosteroids developed BC, compared to 5.1% of the non-users (with an HR = 3.41 per-allele within corticosteroid users). In comparison, there are no differences in BC risk within the reference allele homozygotes. Overall, this work highlights the clinical relevance of gene-drug interactions in disease risk and provides a roadmap for repurposing biobanks in drug repositioning and precision medicine.

Gene-teratogen interactions influence the penetrance of birth defects by altering Hedgehog signaling strength.

Birth defects result from interactions between genetic and environmental factors, but the mechanisms remain poorly understood. We find that mutations and teratogens interact in predictable ways to cause birth defects by changing target cell sensitivity to Hedgehog (Hh) ligands. These interactions converge on a membrane protein complex, the MMM complex, that promotes degradation of the Hh transducer Smoothened (SMO). Deficiency of the MMM component MOSMO results in elevated SMO and increased Hh signaling, causing multiple birth defects. In utero exposure to a teratogen that directly inhibits SMO reduces the penetrance and expressivity of birth defects in Mosmo-/- embryos. Additionally, tissues that develop normally in Mosmo-/- embryos are refractory to the teratogen. Thus, changes in the abundance of the protein target of a teratogen can change birth defect outcomes by quantitative shifts in Hh signaling. Consequently, small molecules that re-calibrate signaling strength could be harnessed to rescue structural birth defects.

The local environment and germline genetic variation predict cancer risk in the UK Biobank prospective cohort.

BACKGROUND: There is a growing body of evidence on the effect of the local environment exposure on cancer susceptibility. Nonetheless, several of the associations remain controversial. Moreover, our understanding of the possible interaction between the local environment and the genetic variability is still very limited. OBJECTIVE: The aim of this study was to clarify the role of the local environment and its possible interplay with genetics on common cancers development. METHODS: Using the UK Biobank (UKBB) prospective cohort, we selected 12 local environment exposures: nitrogen oxides, nitrogen dioxides, particulate matter (10 and 2.5 µm), noise pollution, urban traffic, living distance from the coast, percentage of greenspace, natural environment, water, and domestic garden within 1000 m from the residential coordinates of each participant. All these exposures were tested for association with 17 different types of cancer for a total of 53,270 cases and 302,645 controls. Additionally, a polygenic score (PGS) was computed for each cancer, to test possible gene-environment interactions. Finally, mediation analyses were carried out. RESULTS: Thirty-six statistically significant associations considering multiple testing (p < 2.19 × 10-4) were observed. Among the novel associations we observed that individuals living farther from the coast had a higher risk of developing prostate cancer (OR = 1.13, CI95% = 1.06-1.20, P = 1.98 × 10-4). This association was partially mediated by physical activity (indirect effect (IE) = -8.48 × 10-7) and the time spent outdoor (IE = 9.07 × 10-6). All PGSs showed statistically significant associations. Finally, genome-environment interaction analysis showed that local environment and genetic variability affect cancer risk independently. DISCUSSION: Living close to the coast and air pollution were associated with a decreased risk of prostate cancer and skin melanoma, respectively. These findings from the UKBB support the role of the local environment on cancer development, which is independent from genetics and may be mediated by several lifestyle factors.

Epigenetics, Nutrition, and the Brain: Improving Mental Health through Diet.

The relationship between nutrition and brain health is intricate. Studies suggest that nutrients during early life impact not only human physiology but also mental health. Although the exact molecular mechanisms that depict this relationship remain unclear, there are indications that environmental factors such as eating, lifestyle habits, stress, and physical activity, influence our genes and modulate their function by epigenetic mechanisms to shape mental health outcomes. Epigenetic mechanisms act as crucial link between genes and environmental influences, proving that non-genetic factors could have enduring effects on the epigenome and influence health trajectories. We review studies that demonstrated an epigenetic mechanism of action of nutrition on mental health, focusing on the role of specific micronutrients during critical stages of brain development. The methyl-donor micronutrients of the one-carbon metabolism, such as choline, betaine, methionine, folic acid, VitB6 and VitB12 play critical roles in various physiological processes, including DNA and histone methylation. These micronutrients have been shown to alter gene function and susceptibility to diseases including mental health and metabolic disorders. Understanding how micronutrients influence metabolic genes in humans can lead to the implementation of early nutritional interventions to reduce the risk of developing metabolic and mental health disorders later in life.

Polygene by environment interactions predicting depressive outcomes.

Depression is a major public health problem with a continued need to uncover its etiology. Current models of depression contend that gene-by-environment (G × E) interactions influence depression risk, and further, that depression is polygenic. Thus, recent models have emphasized two polygenic approaches: a hypothesis-driven multilocus genetic profile score (MGPS; "MGPS × E") and a polygenic risk score (PRS; "PRS × E") derived from genome-wide association studies (GWAS). This review for the first time synthesizes current knowledge on polygene by environment "P × E" interaction research predicting primarily depression-related outcomes, and in brief, neurobiological outcomes. The "environment" of focus in this project is stressful life events. It further discusses findings in the context of differential susceptibility and diathesis-stress theories-two major theories guiding G × E work. This synthesis indicates that, within the MGPS literature, polygenic scores based on the serotonin system, the HPA axis, or across multiple systems, interact with environmental stress exposure to predict outcomes at multiple levels of analyses and most consistently align with differential susceptibility theory. Depressive outcomes are the most studied, but neuroendocrine, and neuroimaging findings are observed as well. By contrast, vast methodological differences between GWAS-based PRS studies contribute to mixed findings that yield inconclusive results.

Gene-environment interaction in type 2 diabetes in Korean cohorts: Interaction of a type 2 diabetes polygenic risk score with triglyceride and cholesterol on fasting glucose levels.

Type 2 diabetes (T2D) is caused by genetic and environmental factors as well as gene-environment interactions. However, these interactions have not been systematically investigated. We analyzed these interactions for T2D and fasting glucose levels in three Korean cohorts, HEXA, KARE, and CAVAS, using the baseline data with a multiple regression model. Two polygenic risk scores for T2D (PRST2D ) and fasting glucose (PRSFG ) were calculated using 488 and 82 single nucleotide polymorphisms (SNP) for T2D and fasting glucose, respectively, which were extracted from large-scaled genome-wide association studies with multiethnic data. Both lifestyle risk factors and T2D-related biochemical measurements were assessed. The effect of interactions between PRST2D -triglyceride (TG) and PRST2D -total cholesterol (TC) on fasting glucose levels was observed as follows: ß ± SE = 0.0005 ± 0.0001, p = 1.06 × 10-19 in HEXA, ß ± SE = 0.0008 ± 0.0001, p = 2.08 × 10-8 in KARE for TG; ß ± SE = 0.0006 ± 0.0001, p = 2.00 × 10-6 in HEXA, ß ± SE = 0.0020 ± 0.0004, p = 2.11 × 10-6 in KARE, ß ± SE = 0.0007 ± 0.0004, p = 0.045 in CAVAS for TC. PRST2D -based classification of the participants into four groups showed that the fasting glucose levels in groups with higher PRST2D were more adversely affected by both the TG and TC. In conclusion, blood TG and TC levels may affect the fasting glucose level through interaction with T2D genetic factors, suggesting the importance of consideration of gene-environment interaction in the preventive medicine of T2D.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.

BACKGROUND: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. METHODS: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. RESULTS: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). CONCLUSIONS: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Dynamic RNA Fitness Landscapes of a Group I Ribozyme during Changes to the Experimental Environment.

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1-48 mM MgCl2). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.

Environmental influences on childhood asthma: Allergens.

Allergen exposure is associated with the development of allergen-specific sensitization, but their relationship is influenced by other contemporaneous exposures (such as microbial exposure) and the genetic predisposition of the host. Clinical outcomes of the primary prevention studies that tested the effectiveness of allergen avoidance in pregnancy and early life on the subsequent development of sensitization and asthma published to date are inconsistent. Therefore, we cannot provide any evidence-based advice on the use of allergen avoidance for the primary prevention of these conditions. The evidence about the impact of allergen exposure among and among sensitized children with asthma is more consistent, and the combination of sensitization and high exposure to sensitizing allergen increases airway inflammation, triggers symptoms, adversely impacts upon disease control, and is associated with poorer lung function in preschool age. However, there are differing opinions about the role of inhalant allergen avoidance in asthma management, and recommendations differ in different guidelines. Evidence from more recent high-quality trials suggests that mite allergen-impermeable bed encasings reduce hospital attendance with asthma attacks and that multifaceted targeted environmental control improves asthma control in children. We therefore suggest a pragmatic approach to allergen avoidance in the management of childhood asthma for clinical practice, including the recommendations to: (1) tailor the intervention to the patient's sensitization and exposure status by using titer of allergen-specific IgE antibodies and/or the size of the skin test as indicators of potential response; (2) use a multifaceted allergen control regime to reduce exposure as much as possible; and (3) start intervention as early as possible upon diagnosis.

Robust Bayesian variable selection for gene-environment interactions.

Gene-environment (G× E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G× E studies have been commonly encountered, leading to the development of a broad spectrum of robust regularization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a fully Bayesian robust variable selection method for G× E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, for the robust sparse group selection, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects robustly. An efficient Gibbs sampler has been developed to facilitate fast computation. Extensive simulation studies, analysis of diabetes data with single-nucleotide polymorphism measurements from the Nurses' Health Study, and The Cancer Genome Atlas melanoma data with gene expression measurements demonstrate the superior performance of the proposed method over multiple competing alternatives.

Gene-environment interactions in the associations of PFAS exposure with insulin sensitivity and beta-cell function in a Faroese cohort followed from birth to adulthood.

BACKGROUND: Exposure to perfluoroalkyl substances (PFAS) has been associated with changes in insulin sensitivity and pancreatic beta-cell function in humans. Genetic predisposition to diabetes may modify these associations; however, this hypothesis has not been yet studied. OBJECTIVES: To evaluate genetic heterogeneity as a modifier in the PFAS association with insulin sensitivity and pancreatic beta-cell function, using a targeted gene-environment (GxE) approach. METHODS: We studied 85 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes, in 665 Faroese adults born in 1986-1987. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord whole blood at birth and in participants' serum from age 28 years. We calculated the Matsuda-insulin sensitivity index (ISI) and the insulinogenic index (IGI) based on a 2 h-oral glucose tolerance test performed at age 28. Effect modification was evaluated in linear regression models adjusted for cross-product terms (PFAS*SNP) and important covariates. RESULTS: Prenatal and adult PFOS exposures were significantly associated with decreased insulin sensitivity and increased beta-cell function. PFOA associations were in the same direction but attenuated compared to PFOS. A total of 58 SNPs were associated with at least one PFAS exposure variable and/or Matsuda-ISI or IGI in the Faroese population and were subsequently tested as modifiers in the PFAS-clinical outcome associations. Eighteen SNPs showed interaction p-values (PGxE) < 0.05 in at least one PFAS-clinical outcome association, five of which passed False Discovery Rate (FDR) correction (PGxE-FDR<0.20). SNPs for which we found stronger evidence for GxE interactions included ABCA1 rs3890182, FTO rs9939609, FTO rs3751812, PPARG rs170036314 and SLC12A3 rs2289116 and were more clearly shown to modify the PFAS associations with insulin sensitivity, rather than with beta-cell function. DISCUSSION: Findings from this study suggest that PFAS-associated changes in insulin sensitivity could vary between individuals as a result of genetic predisposition and warrant replication in independent larger populations.

The phenotypic associations and gene-environment underpinnings of socioeconomic status and diurnal cortisol secretion in adolescence.

While converging evidence suggests that both environmental and genetic factors underlie variations in diurnal cortisol, the extent to which these sources of influence vary according to socioeconomic status (SES) has seldom been investigated, particularly in adolescence. To investigate whether a distinct genetic and environmental contribution to youth's diurnal cortisol secretion emerges according to family SES and whether the timing of these experiences matters. Participants were 592 twin pairs, who mostly came from middle-income and intact families and for whom SES was measured in childhood and adolescence. Diurnal cortisol was assessed at age 14 at awakening, 30 min later, in the afternoon and evening over four nonconsecutive days. SES-cortisol phenotypic associations were specific to the adolescence period. Specifically, higher awakening cortisol levels were detected in wealthier backgrounds, whereas higher cortisol awakening response (CAR) and diurnal changes were present at both ends of the SES continuum. Moreover, smaller genetic contributions emerged for awakening cortisol in youth from poorer compared to wealthier backgrounds. The results suggest that the relative contribution of inherited factors to awakening cortisol secretion may be enhanced or suppressed depending on the socio-family context, which may help to decipher the mechanisms underlying later adjustment.

Parental rejection in early adolescence predicts a persistent ADHD symptom trajectory across adolescence.

Despite a general decrease of attention-deficit/hyperactivity disorder (ADHD) symptoms during adolescence, these may persist in some individuals but not in others. Prior cross-sectional studies have shown that parenting style and their interaction with candidate genes are associated with ADHD symptoms. However, there is a lack of longitudinal research examining the independent and interactive effects of parenting and plasticity genes in predicting the course of attention-deficit/hyperactivity disorder (ADHD) symptoms across adolescence. Here, we investigated how children perceived their parents' parenting style (i.e., rejection, overprotection, and emotional warmth) at the age of 11, and their interaction with DRD4, MAOA, and 5-HTTLPR genotypes on parent-reported ADHD symptoms at three time points (mean ages 11.1, 13.4, and 16.2 years) in 1730 adolescents from the TRacking Adolescents' Individual Lives Survey (TRAILS). Growth Mixture Modeling in Mplus identified four ADHD symptom trajectories: low, moderate stable, high decreasing, and high persistent. Perceived parental rejection predicted class membership in the high persistent trajectory compared to the other classes (p < 0.001, odds ratios between 2.14 and 3.74). Gene-environment interactions were not significantly related to class membership. Our results indicate a role of perceived parental rejection in the persistence of ADHD symptoms. Perceived parental rejection should, therefore, be taken into consideration during prevention and treatment of ADHD in young adolescents.

Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors.

Asthma is a complex heterogeneous disease caused by gene-environment interactions. Although numerous genome-wide association studies have been conducted, these interactions have not been systemically investigated. We sought to identify genetic factors associated with the asthma phenotype in 66,857 subjects from the Health Examination Study, Cardiovascular Disease Association Study, and Korea Association Resource Study cohorts. We investigated asthma-associated gene-environment (smoking status) interactions at the level of single nucleotide polymorphisms, genes, and gene sets. We identified two potentially novel (SETDB1 and ZNF8) and five previously reported (DM4C, DOCK8, MMP20, MYL7, and ADCY9) genes associated with increased asthma risk. Numerous gene ontology processes, including regulation of T cell differentiation in the thymus (GO:0033081), were significantly enriched for asthma risk. Functional annotation analysis confirmed the causal relationship between five genes (two potentially novel and three previously reported genes) and asthma through genome-wide functional prediction scores (combined annotation-dependent depletion, deleterious annotation of genetic variants using neural networks, and RegulomeDB). Our findings elucidate the genetic architecture of asthma and improve the understanding of its biological mechanisms. However, further studies are necessary for developing preventive treatments based on environmental factors and understanding the immune system mechanisms that contribute to the etiology of asthma.

Integrative analysis reveals mouse strain-dependent responses to acute ozone exposure associated with airway macrophage transcriptional activity.

Acute ozone (O3) exposure is associated with multiple adverse cardiorespiratory outcomes, the severity of which varies across individuals in human populations and inbred mouse strains. However, molecular determinants of response, including susceptibility biomarkers that distinguish who will develop severe injury and inflammation, are not well characterized. We and others have demonstrated that airway macrophages (AMs) are an important resident immune cell type that are functionally and transcriptionally responsive to O3 inhalation. Here, we sought to explore influences of strain, exposure, and strain-by-O3 exposure interactions on AM gene expression and identify transcriptional correlates of O3-induced inflammation and injury across six mouse strains, including five Collaborative Cross (CC) strains. We exposed adult mice of both sexes to filtered air (FA) or 2 ppm O3 for 3 h and measured inflammatory and injury parameters 21 h later. Mice exposed to O3 developed airway neutrophilia and lung injury with strain-dependent severity. In AMs, we identified a common core O3 transcriptional response signature across all strains, as well as a set of genes exhibiting strain-by-O3 exposure interactions. In particular, a prominent gene expression contrast emerged between a low- (CC017/Unc) and high-responding (CC003/Unc) strain, as reflected by cellular inflammation and injury. Further inspection indicated that differences in their baseline gene expression and chromatin accessibility profiles likely contribute to their divergent post-O3 exposure transcriptional responses. Together, these results suggest that aspects of O3-induced respiratory responses are mediated through altered AM transcriptional signatures and further confirm the importance of gene-environment interactions in mediating differential responsiveness to environmental agents.

The role of environmental exposures and gene-environment interactions in the etiology of systemic lupus erythematous.

Systemic lupus erythematosus (SLE) is a complex, chronic autoimmune disease, whose etiology includes both genetic and environmental factors. Individual genetic risk factors likely only account for about one-third of observed heritability among individuals with a family history of SLE. A large portion of the remaining risk may be attributable to environmental exposures and gene-environment interactions. This review focuses on SLE risk associated with environmental factors, ranging from chemical and physical environmental exposures to lifestyle behaviors, with the weight of evidence supporting positive associations between SLE and occupational exposure to crystalline silica, current smoking, and exogenous estrogens (e.g., oral contraceptives and postmenopausal hormones). Other risk factors may include lifestyle behaviors (e.g., dietary intake and sleep) and other exposures (e.g., ultraviolet [UV] radiation, air pollution, solvents, pesticides, vaccines and medications, and infections). Alcohol use may be associated with decreased SLE risk. We also describe the more limited body of knowledge on gene-environment interactions and SLE risk, including IL-10, ESR1, IL-33, ITGAM, and NAT2 and observed interactions with smoking, UV exposure, and alcohol. Understanding genetic and environmental risk factors for SLE, and how they may interact, can help to elucidate SLE pathogenesis and its clinical heterogeneity. Ultimately, this knowledge may facilitate the development of preventive interventions that address modifiable risk factors in susceptible individuals and vulnerable populations.

Genetic, epigenetic, and environmental contributions to neural tube closure.

The formation of the embryonic brain and spinal cord begins as the neural plate bends to form the neural folds, which meet and adhere to close the neural tube. The neural ectoderm and surrounding tissues also coordinate proliferation, differentiation, and patterning. This highly orchestrated process is susceptible to disruption, leading to neural tube defects (NTDs), a common birth defect. Here, we highlight genetic and epigenetic contributions to neural tube closure. We describe an online database we created as a resource for researchers, geneticists, and clinicians. Neural tube closure is sensitive to environmental influences, and we discuss disruptive causes, preventative measures, and possible mechanisms. New technologies will move beyond candidate genes in small cohort studies toward unbiased discoveries in sporadic NTD cases. This will uncover the genetic complexity of NTDs and critical gene-gene interactions. Animal models can reveal the causative nature of genetic variants, the genetic interrelationships, and the mechanisms underlying environmental influences.