Importance Of Gene-environment Interactions Research Articles

Insights into the Molecular Mechanisms of Genetic Predisposition to Hematopoietic Malignancies: The Importance of Gene-Environment Interactions.

The recognition of host genetic factors underlying susceptibility to hematopoietic malignancies has increased greatly over the last decade. Historically, germline predisposition was thought to primarily affect the young. However, emerging data indicate that hematopoietic malignancies that develop in people of all ages across the human lifespan can derive from germline predisposing conditions and are not exclusively observed in younger individuals. The age at which hematopoietic malignancies manifest appears to correlate with distinct underlying biological pathways. Progression from having a deleterious germline variant to being diagnosed with overt malignancy involves complex, multistep gene-environment interactions with key external triggers, such as infection and inflammatory stimuli, driving clonal progression. Understanding the mechanisms by which predisposed clones transform under specific pressures may reveal strategies to better treat and even prevent hematopoietic malignancies from occurring.Recent unbiased genome-wide sequencing studies of children and adults with hematopoietic malignancies have revealed novel genes in which disease-causing variants are of germline origin. This paradigm shift is spearheaded by findings in myelodysplastic syndrome/acute myeloid leukemia (MDS/AML) as well as acute lymphoblastic leukemia, but it also encompasses other cancer types. Although not without challenges, the field of genetic cancer predisposition is advancing quickly, and a better understanding of the genetic basis of hematopoietic malignancies risk affects therapeutic decisions as well as genetic counseling and testing of at-risk family members.

Wood cookstove use is associated with gastric cancer in Central America and mediated by host genetics

Biomass cookstove food preparation is linked to aero-digestive cancers, mediated by ingested and inhaled carcinogens (e.g., heterocyclic amines, and polycyclic aromatic hydrocarbons). We investigated the association between gastric adenocarcinoma, wood cookstove use, H. pylori CagA infection and risk modification by variants in genes that metabolize and affect the internal dose of carcinogens. We conducted a population-based, case–control study (814 incident cases, 1049 controls) in rural Honduras, a high-incidence region with a homogeneous diet and endemic H. pylori infection, primarily with the high-risk CagA genotype. We investigated factors including wood cookstove use, H. pylori CagA serostatus, and 15 variants from 7 metabolizing genes, and the interactions between wood stove use and the genetic variants. Male sex (OR 2.0, 1.6–2.6), age (OR 1.04, 1.03–1.05), wood cookstove use (OR 2.3, 1.6–3.3), and CagA serostatus (OR 3.5, 2.4–5.1) and two SNPs in CYP1B1 (rs1800440 and rs1056836) were independently associated with gastric cancer in multivariate analysis. In the final multivariate model, a highly significant interaction (OR 3.1, 1.2–7.8) was noted between wood cookstove use and the rs1800440 metabolizing genotype, highlighting an important gene-environment interaction. Lifetime wood cookstove use associates with gastric cancer risk in the high-incidence regions of Central America, and the association is dependent on the rs1800440 genotype in CYP1B1. H. pylori CagA infection, wood cookstove use and the rs1800440 genotype, all of which are highly prevalent, informs who is at greatest risk from biomass cookstove use.

Gene-environment interaction identification via penalized robust divergence.

In high-throughput cancer studies, gene-environment interactions associated with outcomes have important implications. Some commonly adopted identification methods do not respect the "main effect, interaction" hierarchical structure. In addition, they can be challenged by data contamination and/or long-tailed distributions, which are not uncommon. In this article, robust methods based on -divergence and density power divergence are proposed to accommodate contaminated data/long-tailed distributions. A hierarchical sparse group penalty is adopted for regularized estimation and selection and can identify important gene-environment interactions and respect the "main effect, interaction" hierarchical structure. The proposed methods are implemented using an effective group coordinate descent algorithm. Simulation shows that when contamination occurs, the proposed methods can significantly outperform the existing alternatives with more accurate identification. The proposed approach is applied to the analysis of The Cancer Genome Atlas (TCGA) triple-negative breast cancer data and Gene Environment Association Studies (GENEVA) Type 2 Diabetesdata.

A three-dimensional habitat for C. elegans environmental enrichment

As we learn more about the importance of gene-environment interactions and the effects of environmental enrichment, it becomes evident that minimalistic laboratory conditions can affect gene expression patterns and behaviors of model organisms. In the laboratory, Caenorhabditis elegans is generally cultured on two-dimensional, homogeneous agar plates abundantly covered with axenic bacteria culture as a food source. However, in the wild, this nematode thrives in rotting fruits and plant stems feeding on bacteria and small eukaryotes. This contrast in habitat complexity suggests that studying C. elegans in enriched laboratory conditions can deepen our understanding of its fundamental traits and behaviors. Here, we developed a protocol to create three-dimensional habitable scaffolds for trans-generational culture of C. elegans in the laboratory. Using decellularization and sterilization of fruit tissue, we created an axenic environment that can be navigated throughout and where the microbial environment can be strictly controlled. C. elegans were maintained over generations on this habitat, and showed a clear behavioral bias for the enriched environment. As an initial assessment of behavioral variations, we found that dauer populations in scaffolds exhibit high-frequency, complex nictation behavior including group towering and jumping behavior.

P5540Familial clustering of spontaneous coronary artery dissection

Abstract Background There is increasing evidence that patients with spontaneous coronary artery dissection (SCAD) have an underlying genetic susceptibility (Goel et al JAMA Intern Med175:821–826, 2015). Moreover, in a collaborative study involving 1,055 SCAD cases and 7,190 controls, we recently reported the first risk allele for SCAD, a variant (rs9349379-A) in the PHACTR1/EDN1 genetic locus (Adlam et al J Amer Coll Cardiol73:58–66, 2019). Purpose We sought to determine the clinical characteristics and initial genetic data for 11 families, in which more than one member has had an episode of SCAD. Methods Participants were recruited largely via a social media platform. Informed consent was obtained in all cases for analysis of genetic information using whole genome sequencing, as well as collection of clinical information. SCAD was confirmed by review of coronary angiogram images and clinical data collected by phone interview, as well as review of specialist letters and hospital records. Results Of 235 participants recruited to date, 23 cases showed familial clustering involving sister-sister pairs in six families, three first-degree cousins in one family (picture), two first-degree cousins in two families, a mother-son pair, and a family with concordant monozygotic twins, that is both twins having had SCAD. In an additional family, SCAD is discordant in monozygotic twins. A comparison of symptoms, age at SCAD, clinical syndrome, cardiovascular risk factors, SCAD risk factors, environmental triggers, SCAD location, acute management, left ventricular function and recurrent SCAD events in these families versus isolated cases, will be presented. Three sister-sister pairs have undergone whole genome sequencing and these data sets are undergoing segregation analysis to identify rare variants that are present exclusively in affected family members. Family E Pedigree. Shaded circles represent first cousins affected with SCAD. The top number represents age (in years) of the SCAD event and the bottom number represents current age (in years). Conclusions To our knowledge, this is the largest assembly of SCAD cases with familial clustering reported to date. It provides strong evidence supporting an underlying genetic basis for SCAD, which most likely is a multi-genic disorder that also involves important gene-environment interactions.

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ.

Obesity Accelerates Alzheimer-Related Pathology in APOE4 but not APOE3 Mice.

Alzheimer’s disease (AD) risk is modified by both genetic and environmental risk factors, which are believed to interact to cooperatively modify pathogenesis. Although numerous genetic and environmental risk factors for AD have been identified, relatively little is known about potential gene-environment interactions in regulating disease risk. The strongest genetic risk factor for late-onset AD is the ε4 allele of apolipoprotein E (APOE4). An important modifiable risk factor for AD is obesity, which has been shown to increase AD risk in humans and accelerate development of AD-related pathology in rodent models. Potential interactions between APOE4 and obesity are suggested by the literature but have not been thoroughly investigated. In the current study, we evaluated this relationship by studying the effects of diet-induced obesity (DIO) in the EFAD mouse model, which combines familial AD transgenes with human APOE3 or APOE4. Male E3FAD and E4FAD mice were maintained for 12 weeks on either a control diet or a Western diet high in saturated fat and sugars. We observed that metabolic outcomes of DIO were similar in E3FAD and E4FAD mice. Importantly, our data showed a significant interaction between diet and APOE genotype on AD-related outcomes in which Western diet was associated with robust increases in amyloid deposits, β-amyloid burden, and glial activation in E4FAD but not in E3FAD mice. These findings demonstrate an important gene-environment interaction in an AD mouse model that suggests that AD risk associated with obesity is strongly influenced by APOE genotype.

The importance of gene-environment interactions in human obesity.

The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.

Gene–Environment Interaction from International Cohorts: Impact on Development and Evolution of Occupational and Environmental Lung and Airway Disease

Environmental and occupational pulmonary diseases impose a substantial burden of morbidity and mortality on the global population. However, it has been long observed that only some of those who are exposed to pulmonary toxicants go on to develop disease; increasingly, it is being recognized that genetic differences may underlie some of this person-to-person variability. Studies performed throughout the globe are demonstrating important gene-environment interactions for diseases as diverse as chronic beryllium disease, coal workers' pneumoconiosis, silicosis, asbestosis, byssinosis, occupational asthma, and pollution-associated asthma. These findings have, in many instances, elucidated the pathogenesis of these highly complex diseases. At the same time, however, translation of this research into clinical practice has, for good reasons, proceeded slowly. No genetic test has yet emerged with sufficiently robust operating characteristics to be clearly useful or practicable in an occupational or environmental setting. In addition, occupational genetic testing raises serious ethical and policy concerns. Therefore, the primary objective must remain ensuring that the workplace and the environment are safe for all.

Integrative analysis of gene-environment interactions under a multi-response partially linear varying coefficient model.

Consider the integrative analysis of genetic data with multiple correlated response variables. The goal is to identify important gene-environment (G × E) interactions along with main gene and environment effects that are associated with the responses. The homogeneity and heterogeneity models can be adopted to describe the genetic basis of multiple responses. To accommodate possible nonlinear effects of some environment effects, a multi-response partially linear varying coefficient model is assumed. Penalization is adopted for marker selection. The proposed penalization method can select genetic variants with G × E interactions, no G × E interactions, and no main effects simultaneously. It adopts different penalties to accommodate the homogeneity and heterogeneity models. The proposed method can be effectively computed using a coordinate descent algorithm. Simulation study and the analysis of Health Professionals Follow-up Study, which has two correlated continuous traits, SNP measurements and multiple environment effects, show superior performance of the proposed method over its competitors.

Identifying gene-environment and gene-gene interactions using a progressive penalization approach.

In genomic studies, identifying important gene-environment and gene-gene interactions is a challenging problem. In this study, we adopt the statistical modeling approach, where interactions are represented by product terms in regression models. For the identification of important interactions, we adopt penalization, which has been used in many genomic studies. Straightforward application of penalization does not respect the "main effect, interaction" hierarchical structure. A few recently proposed methods respect this structure by applying constrained penalization. However, they demand very complicated computational algorithms and can only accommodate a small number of genomic measurements. We propose a computationally fast penalization method that can identify important gene-environment and gene-gene interactions and respect a strong hierarchical structure. The method takes a stagewise approach and progressively expands its optimization domain to account for possible hierarchical interactions. It is applicable to multiple data types and models. A coordinate descent method is utilized to produce the entire regularized solution path. Simulation study demonstrates the superior performance of the proposed method. We analyze a lung cancer prognosis study with gene expression measurements and identify important gene-environment interactions.

EPA-1461 – Gene x environment interactions in suicidal behaviour

The causes of why certain people engage in suicidal behaviors involve both environmental and genetic factors, and interactions in-between. The aim here was to study certain aspects of stress-vulnerability in SA, i.e. the association of polymorphisms in genes which e.g. regulate the neuroendocrine hypothalamic-pituitary-adrenal (HPA) axis stress-response, as well as the importance of gene-environment interactions (GxE). We studied genetic associations in the context of parent-child inheritance, as well as gene-environment interaction (GxE) patterns considering life timing of trauma and gender, concerning polymorphisms in candidate hypothalamic-pituitary-adrenal (HPA) axis gene networks, as well as on a genome-wide scale. For GxEs, we assessed exposures to physical assault (PA, below or over age of 18) or cumulative, lifetime exposure to a panel of stressful life events (SLEs) in male and females. Studies were conducted by a family-based design (n=660 trios) in relation to the outcome of severe lifetime SA in the offspring. We have previously shown the associations of several HPA-regulatory candidate genes. The current results aim to present an extension involving more genes and make an attempt to shift towards polygenetic associations, which may lead to a better understanding of etiology. We investigate the patterns of GxE vs non-GxE associations, with the aim to better define the genetic components of the stress diathesis model for suicidal behaviors.

On Lung Function and Interactions Using Genome-Wide Data

On Lung Function and Interactions Using Genome-Wide Data

Mitochondrial dynamics and autophagy aid in removal of persistent mitochondrial DNA damage in Caenorhabditis elegans

Mitochondria lack the ability to repair certain helix-distorting lesions that are induced at high levels in mitochondrial DNA (mtDNA) by important environmental genotoxins and endogenous metabolites. These lesions are irreparable and persistent in the short term, but their long-term fate is unknown. We report that removal of such mtDNA damage is detectable by 48 h in Caenorhabditis elegans, and requires mitochondrial fusion, fission and autophagy, providing genetic evidence for a novel mtDNA damage removal pathway. Furthermore, mutations in genes involved in these processes as well as pharmacological inhibition of autophagy exacerbated mtDNA damage-mediated larval arrest, illustrating the in vivo relevance of removal of persistent mtDNA damage. Mutations in genes in these pathways exist in the human population, demonstrating the potential for important gene–environment interactions affecting mitochondrial health after genotoxin exposure.

Probiotics for the prevention of allergic disease

Probiotics for the prevention of allergic disease

Prevalence of Nontuberculous Mycobacterial Lung Disease in U.S. Medicare Beneficiaries

Pulmonary nontuberculous mycobacteria (PNTM) are an important cause of morbidity among older adults in the United States, but national prevalence estimates are lacking. To describe the prevalence and trends of PNTM disease among adults aged 65 years or older throughout the United States. A nationally representative 5% sample of Medicare Part B beneficiaries was analyzed from 1997 to 2007. Demographic and medical claims data were compiled and prevalence estimates for PNTM and selected comorbidities were calculated and trends over time evaluated. Logistic regression was used to identify demographic and geographic factors associated with PNTM. From 1997 to 2007, the annual prevalence significantly increased from 20 to 47 cases/100,000 persons, or 8.2% per year. The period prevalence was 112 cases/100,000 persons, although prevalence was twofold higher among Asians/Pacific Islanders than among whites (228 vs. 116 cases/100,000 persons). Western states had the highest period prevalence at 149 cases/100,000 persons, with Hawaii having the highest prevalence at 396 cases/100,000 persons, followed by southeastern states, which had a period prevalence of 131 cases/100,000 persons. PNTM cases had more comorbid conditions than noncases and were 40% more likely to die than noncases. Women were 1.4 times more likely to be a PNTM case than men. Relative to whites, Asians/Pacific Islanders were twice as likely to be a case, whereas blacks were half as likely. The prevalence of PNTM is increasing across all regions of the United States and among both men and women. Significant racial/ethnic and geographic differences suggest important gene-environment interactions.

Genome-wide association study reveals class I MHC–restricted T cell–associated molecule gene (CRTAM) variants interact with vitamin D levels to affect asthma exacerbations

It has recently been shown that vitamin D deficiency can increase asthma development and severity and that variations in vitamin D receptor genes are associated with asthma susceptibility. We sought to find genetic factors that might interact with vitamin D levels to affect the risk of asthma exacerbation. We conducted a genome-wide study of gene-vitamin D interaction on asthma exacerbations using population-based and family-based approaches on 403 subjects and trios from the Childhood Asthma Management Program. Twenty-three polymorphisms with significant interactions were studied in a replication analysis in 584 children from a Costa Rican cohort. We identified 3 common variants in the class I MHC-restricted T cell-associated molecule gene (CRTAM) that were associated with an increased rate of asthma exacerbations based on the presence of a low circulating vitamin D level. These results were replicated in a second independent population (unadjusted combined interaction, P= .00028-.00097; combined odds ratio, 3.28-5.38). One variant, rs2272094, is a nonsynonymous coding polymorphism of CRTAM. Functional studies on cell lines confirmed the interaction of vitamin D and rs2272094 on CRTAM expression. CRTAM is highly expressed in activated human CD8(+) and natural killer T cells, both of which have been implicated in asthmatic patients. The findings highlight an important gene-environment interaction that elucidates the role of vitamin D and CD8(+) and natural killer T cells in asthma exacerbation in a genome-wide gene-environment interaction study that has been replicated in an independent population. The results suggest the potential importance of maintaining adequate vitamin D levels in subsets of high-risk asthmatic patients.

Gene-Environment Interaction in Childhood Asthma

The importance of early life environmental influences on the etiology of asthma is implied by the observed geographic and temporal variation in the prevalence of the disease among children. There is evidence pointing to the role of exposure to allergen, various aspects of diet and hygiene-related factors in the etiology of asthma. There is also evidence that heritable factors influence the impact of hygiene-related exposures on the risk of having asthma. A number of important gene-environment interactions have been identified. These interactions point to the biology of environmental exposures as the involved genetic variation is suggestive of certain underlying mechanisms. Polymorphisms within genes coding for the toll-like receptor-lipopolysaccharide (TLR-LPS) signalling pathway may underlie variations in effects of hygiene-related exposures, including specifically endotoxin, on the risk of developing allergic sensitization and allergic disease. This review presents recent findings illustrating the role of gene-environment interactions in childhood asthma susceptibility.

Using the laboratory to predict recurrent venous thrombosis

Characterisation of heritable thrombophilic defects has facilitated an understanding of the complex mechanisms influencing risk of venous thromboembolism. In parallel with this, the importance of gene-environment interaction in the development of this disease has become apparent. However, testing for a limited number of heritable thrombophilic defects (first generation thrombophilia testing) has not been shown to predict likelihood of recurrent venous thrombosis to any useful degree. This paradox whereby thrombophilia testing identifies defects associated with an increased risk of a first venous thrombosis but not of a particularly high risk of recurrence is likely the result of limitations imposed by a limited dichotomous testing strategy compounded by test inaccuracy and imprecision. Consequently, the observed intermediate phenotype (defined by limited dichotomous testing) is not concordant with the risk of recurrent venous thrombosis. Whilst a simple dichotomous testing strategy for a limited number of heritable thrombophilic defects has not been shown to have useful clinical predictive value, proof-of-principle is emerging for testing of multiple genetic factors in predicting the likelihood of recurrent thrombosis. In addition, recent studies indicate that measurement of the global activity of the coagulation system using either biomarkers or measuring the thrombin generating potential (second generation thrombophilia testing) may have useful clinical predictive value for recurrent thrombosis. The assessment of the intermediate phenotype by global coagulation tests and genome-wide mutation and SNP (single nucleotide polymorphisms) detection may provide complimentary approaches to the quantification of risk of recurrence and enable a move towards more patient-focussed rather than disease-focussed care.

866: Two-step Bayesian model averaging process documents gene-environment interactions associated with spontaneous preterm birth

Identification of important gene-environment (GxE) interactions is necessary to advance prevention and treatment efforts for spontaneous preterm birth (sPTB). Complicating this search is the challenge of identifying meaningful interactions in highly dimensional datasets. We report a novel method of testing GxE interactions to document risk association in sPTB.